{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Programming Exercise 8: Anomaly Detection and Recommender Systems"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.io #Used to load the OCTAVE *.mat files\n",
    "import scipy.optimize #Use for fmincg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1 Anomaly detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "datafile = 'data/ex8data1.mat'\n",
    "mat = scipy.io.loadmat( datafile )\n",
    "X = mat['X']\n",
    "ycv = mat['yval']\n",
    "Xcv = mat['Xval']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Visualize the data\n",
    "def plotData(myX, newFig=False):\n",
    "    if newFig:\n",
    "        plt.figure(figsize=(8,6))\n",
    "    plt.plot(myX[:,0],myX[:,1],'b+')\n",
    "    plt.xlabel('Latency [ms]',fontsize=16)\n",
    "    plt.ylabel('Throughput [mb/s]',fontsize=16)\n",
    "    plt.grid(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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rrgnr79gR/n3ta8O/u3fHK430wvnww8O2CxfCkUeGK49s7+j168uUyyUmJsLdURAS0NKl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\nIeFkYDhWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11e72bf10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotData(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.1 Gaussian distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def gaus(myX, mymu, mysig2):\n",
    "    \"\"\"\n",
    "    Function to compute the gaussian return values for a feature\n",
    "    matrix, myX, given the already computed mu vector and sigma matrix.\n",
    "    If sigma is a vector, it is turned into a diagonal matrix\n",
    "    Uses a loop over rows; I didn't quite figure out a vectorized implementation.\n",
    "    \"\"\"\n",
    "    m = myX.shape[0]\n",
    "    n = myX.shape[1]\n",
    "    if np.ndim(mysig2) == 1:\n",
    "        mysig2 = np.diag(mysig2)\n",
    "\n",
    "    norm = 1./(np.power((2*np.pi), n/2)*np.sqrt(np.linalg.det(mysig2)))\n",
    "    myinv = np.linalg.inv(mysig2)\n",
    "    myexp = np.zeros((m,1))\n",
    "    for irow in xrange(m):\n",
    "        xrow = myX[irow]\n",
    "        myexp[irow] = np.exp(-0.5*((xrow-mymu).T).dot(myinv).dot(xrow-mymu))\n",
    "    return norm*myexp\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.2 Estimating parameters for a Gaussian"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def getGaussianParams(myX,useMultivariate = True):\n",
    "    \"\"\"\n",
    "    Function that given a feature matrix X that is (m x n)\n",
    "    returns a mean vector and a sigmasquared vector that are\n",
    "    both (n x 1) in shape.\n",
    "    This can do it either as a 1D gaussian for each feature,\n",
    "    or as a multivariate gaussian.\n",
    "    \"\"\"\n",
    "    m = myX.shape[0]\n",
    "    mu = np.mean(myX,axis=0)\n",
    "    if not useMultivariate:\n",
    "        sigma2 = np.sum(np.square(myX-mu),axis=0)/float(m)\n",
    "        return mu, sigma2\n",
    "    else:\n",
    "        sigma2 = ((myX-mu).T.dot(myX-mu))/float(m)\n",
    "        return mu, sigma2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "mu, sig2 = getGaussianParams(X, useMultivariate = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 1.2.1 Visualizing the Gaussian probability contours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def plotContours(mymu, mysigma2, newFig=False, useMultivariate = True):\n",
    "    delta = .5\n",
    "    myx = np.arange(0,30,delta)\n",
    "    myy = np.arange(0,30,delta)\n",
    "    meshx, meshy = np.meshgrid(myx, myy)\n",
    "    coord_list = [ entry.ravel() for entry in (meshx, meshy) ]\n",
    "    points = np.vstack(coord_list).T\n",
    "    myz = gaus(points, mymu, mysigma2)\n",
    "    #if not useMultivariate:\n",
    "    #    myz = gausOrthog(points, mymu, mysigma2)\n",
    "    #else: myz = gausMV(points, mymu, mysigma2)\n",
    "    myz = myz.reshape((myx.shape[0],myx.shape[0]))\n",
    "\n",
    "    if newFig: plt.figure(figsize=(6,4))\n",
    "    \n",
    "    cont_levels = [10**exp for exp in range(-20,0,3)]\n",
    "    mycont = plt.contour(meshx, meshy, myz, levels=cont_levels)\n",
    "\n",
    "    plt.title('Gaussian Contours',fontsize=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Mw4fD0bSpPfz8HNGqlco33LixnU49aNQEcnMlCA5+ht27HxYtZTpqlGopU10L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\njww87gOotruRkpIrqZRiVFSa5AIj+/bdxrhxbZi2ywwLO4fOneUpf3r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pKahZR1rLX2Oi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\nZOKBRBbh8xmkphYgISHvfc71XCQm5n84LiriYfRoU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h3Wqgk83OMVThSr4KlNXKQBM2PE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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11e740f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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du1tzn2oDJSoqE99/74urV6OxfHk/zJ/fHTo6vM/BeTPhw+mcekNJiQTx8Tll/tP09EKE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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11e740a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# First contours without using multivariate gaussian:\n",
    "plotData(X, newFig=True)\n",
    "useMV = False\n",
    "plotContours(*getGaussianParams(X, useMV), newFig=False, useMultivariate = useMV)\n",
    "\n",
    "# Then contours with multivariate gaussian:\n",
    "plotData(X, newFig=True)\n",
    "useMV = True\n",
    "plotContours(*getGaussianParams(X, useMV), newFig=False, useMultivariate = useMV)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.3 Selecting the threshold, $\\epsilon$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def computeF1(predVec, trueVec):\n",
    "    \"\"\"\n",
    "    F1 = 2 * (P*R)/(P+R)\n",
    "    where P is precision, R is recall\n",
    "    Precision = \"of all predicted y=1, what fraction had true y=1\"\n",
    "    Recall = \"of all true y=1, what fraction predicted y=1?\n",
    "    Note predictionVec and trueLabelVec should be boolean vectors.\n",
    "    \"\"\"\n",
    "    #print predVec.shape\n",
    "    #print trueVec.shape\n",
    "    #assert predVec.shape == trueVec.shape\n",
    "    \n",
    "    P, R = 0., 0.\n",
    "    if float(np.sum(predVec)):\n",
    "        P = np.sum([int(trueVec[x]) for x in xrange(predVec.shape[0]) \\\n",
    "                    if predVec[x]]) / float(np.sum(predVec))\n",
    "    if float(np.sum(trueVec)):\n",
    "        R = np.sum([int(predVec[x]) for x in xrange(trueVec.shape[0]) \\\n",
    "                    if trueVec[x]]) / float(np.sum(trueVec))\n",
    "        \n",
    "    return 2*P*R/(P+R) if (P+R) else 0\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def selectThreshold(myycv, mypCVs):\n",
    "    \"\"\"\n",
    "    Function to select the best epsilon value from the CV set\n",
    "    by looping over possible epsilon values and computing the F1\n",
    "    score for each.\n",
    "    \"\"\"\n",
    "    # Make a list of possible epsilon values\n",
    "    nsteps = 1000\n",
    "    epses = np.linspace(np.min(mypCVs),np.max(mypCVs),nsteps)\n",
    "    \n",
    "    # Compute the F1 score for each epsilon value, and store the best \n",
    "    # F1 score (and corresponding best epsilon)\n",
    "    bestF1, bestEps = 0, 0\n",
    "    trueVec = (myycv == 1).flatten()\n",
    "    for eps in epses:\n",
    "        predVec = mypCVs < eps\n",
    "        thisF1 = computeF1(predVec, trueVec)\n",
    "        if thisF1 > bestF1:\n",
    "            bestF1 = thisF1\n",
    "            bestEps = eps\n",
    "            \n",
    "    print \"Best F1 is %f, best eps is %0.4g.\"%(bestF1,bestEps)\n",
    "    return bestF1, bestEps\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best F1 is 0.875000, best eps is 9.075e-05.\n"
     ]
    }
   ],
   "source": [
    "# Using the gaussian parameters from the full training set,\n",
    "# figure out the p-value for each point in the CV set\n",
    "pCVs = gaus(Xcv, mu, sig2)\n",
    "\n",
    "#You should see a value for epsilon of about 8.99e-05.\n",
    "bestF1, bestEps = selectThreshold(ycv,pCVs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def plotAnomalies(myX, mybestEps, newFig = False, useMultivariate = True):\n",
    "    ps = gaus(myX, *getGaussianParams(myX, useMultivariate))\n",
    "    anoms = np.array([myX[x] for x in xrange(myX.shape[0]) if ps[x] < mybestEps])\n",
    "    if newFig: plt.figure(figsize=(6,4))\n",
    "    plt.scatter(anoms[:,0],anoms[:,1], s=80, facecolors='none', edgecolors='r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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SpOHGl8ViCc6cCce+fSG4cOEphg2zQ+/eVmjaVAu6ulpo1ky73KKnpwMTEz2YmTWHsbEe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jFYtbsZInJnoNGs0/i/lBT4DB2Kf9aswRInJ+wZNAgrJ+5G0rlzKM0XrgGNpLQUzy5eRPR//4vN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\nlMRFREQKlJK4iIhIgVISFxERKVD/D8InEtEAIjxAAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11e73dbd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotData(X, newFig=True)\n",
    "plotContours(mu, sig2, newFig=False, useMultivariate=True)\n",
    "plotAnomalies(X, bestEps, newFig=False, useMultivariate=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.4 High dimensional dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Xpart2 shape is  (1000, 11)\n"
     ]
    }
   ],
   "source": [
    "datafile = 'data/ex8data2.mat'\n",
    "mat = scipy.io.loadmat( datafile )\n",
    "Xpart2 = mat['X']\n",
    "ycvpart2 = mat['yval']\n",
    "Xcvpart2 = mat['Xval']\n",
    "print 'Xpart2 shape is ', Xpart2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best F1 is 0.615385, best eps is 3.456e-18.\n",
      "# of anomalies found:  117\n"
     ]
    }
   ],
   "source": [
    "mu, sig2 = getGaussianParams(Xpart2, useMultivariate=False)\n",
    "ps = gaus(Xpart2, mu, sig2)\n",
    "psCV = gaus(Xcvpart2, mu, sig2)\n",
    "\n",
    "# Using the gaussian parameters from the full training set,\n",
    "# figure out the p-value for each point in the CV set\n",
    "pCVs = gaus(Xcvpart2, mu, sig2)\n",
    "\n",
    "# You should see a value epsilon of about 1.38e-18, and 117 anomalies found.\n",
    "bestF1, bestEps = selectThreshold(ycvpart2,pCVs)\n",
    "anoms = [Xpart2[x] for x in xrange(Xpart2.shape[0]) if ps[x] < bestEps]\n",
    "print '# of anomalies found: ',len(anoms)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2 Recommender Systems"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "#### 2.1 Movie ratings dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "datafile = 'data/ex8_movies.mat'\n",
    "mat = scipy.io.loadmat( datafile )\n",
    "Y = mat['Y']\n",
    "R = mat['R']\n",
    "\n",
    "nm, nu = Y.shape\n",
    "# Y is 1682x943 containing ratings (1-5) of 1682 movies on 943 users\n",
    "# a rating of 0 means the movie wasn't rated\n",
    "# R is 1682x943 containing R(i,j) = 1 if user j gave a rating to movie i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average rating for movie 1 (Toy Story): 3.88\n"
     ]
    },
    {
     "data": {
      "image/png": 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y8S6KCaU6PTAPsozv9dBl19iTEojWx4aPOm6iqED0mAfK2lJ4PcNkkjq8xImk\nK04EeeSzqM8S0362DFnAgAYX2T14tsWxqpayuYellGpuLvLuTuOOdrYD3PfMeVw35PDNmb9fJLib\nyyl25rY0/Z7Q5DgLLrS2aNOK4/h0sWHz7vDqm/+9c9SoqAaFupztdwfFsCquGc9E7OWTk51My9v1\nSOXI9prDQt1sisguteet9tvYlhTMX8lCC3tyYSlfjLccgUb3S2HfJj9mn45lWotg7pl2mewMG7Yu\nNZsq7n82hl8+bkYj50xTXsZTLffzeWUJkG53JbFzTQCjH73I4m9EZ+FAAXrKUFEs6npVpW/AZTYn\nhdC1/UV2HRLbGUOHq+LVsiPpp0ROSh82s4W+pnU2mnJKDTqGfRrKyqcvmpbrlAravGZP+8W7+fas\neO5dBiXjsu4Y6xhc4/kYGRF8lrXxTSg1WA75mruncibLh0frraXcrx6zj7Wrcz814epZwhifU/xw\nLvJvtW/qn8j55Pq1rm84SEP8OgMDG1xke0KASVAZacNRjtGW8MhMzh629J8Nui8O7eYs1lwXpsN3\nO2xh5sE+/+h6onwSOZBan5GPXGLpd+ZyQFWz2EdMu8zy2SE1bt+qcxon9ojor6GTY1n9czB3TYpl\n48EISs9aDg4iOEGJawDnqyQWtvNK5kK5l0kzAvCcGUrG17n06X+YLUssTW61819wttdseb6lKFel\ns/1/xq+fNOX6GTHKO9D7Q4t1by4QSWTGUbCRnHx4kB9Nv5ckNbdYf1/oSU7QmuAMa3OCi7swQT3B\nF6ZlioMY+b7TZRsgXnZNNWd76oSPrPb13uu7AfjkZCfcbcUI8PK4LwgMtfzI+rKJ6YjRcU65MK29\ncqgX23PMH/dXjzowu+sa5u3fYlrWr9KBes9HYkR3b8oRtq4QX8Smwb/g4FzGtKR9HOr7IfFFbvRs\nEEtE10zmxrSmuV503DvXCA1j4rVDuOjF6PXjzYcI61fMFHuRcIiTOVR0rJMwmTnpS2l9tD0NssR1\nOY/2xyOwSoTSBD8AMuzMHeC1c69aXLedVrSvKkRebbeDclXDlbKGfHvWXJPMsC7WJESKnnoHEIU0\njTz5oTBjbUxraiVEABLvFoLjm2tDmH3cLETuvs8y6/2eYOFH0lcJA196QCQD5mTY8sO5SCI8LDPy\n23olWx6svcit8aow0KmKOWcUi4msrMXV1i+FIhc3tg6Zz/qEUEq04rk3bmFOSHyhtzi36kIEYN2v\nQSYhApgCBo02AAAgAElEQVSEiEeVZD27sFZWAQtPIbS8xPs+5UCqEHJLZzezaNPBx5zjZBQiM/jU\ntMzGTtybUaUneZwvAZj0ovB/rZkXzHsuZo3txMjvAKEJRvkmMpUfAFhwYDNH0v3xNeTx2+BlnJj4\nPTqbCpa98TnkXr+hEGkdXXepHYkld6wgCecMgU457Ll7Dp5hYlT+u00PizavTohiwnMxTN4+zGK5\njweUNTF3Qg/V28Xkpsfo4C2itH69GEEbjrLunHU0Tm6WGFF/yZOmZV17iw571u5eAGS8e5GKKiGW\n/etf4u2jXa329faz4iPs4R9LXmU0zQuug01lQACcdCVsph++kUIzElpO5T0IT+XltiLPY/KjJ5l9\nrh2TOppHnUd3ig7+jWBh6193vjHPtRDCq9+f91OYp6fL75Npv/l5Au1z+CshGLvsYgY8lMCZslAe\na36A4cHnGPvEBVafa4KvvzAB7llXj8aHjmP3XGWHm2/+aAvuEXb7FXFhJHXaDsCkmVeISImh9LrC\npUEiw//JCpFU1tE1mbWRHwPgE/aOxf0pNWgJJJ73O5iF45tHumOjN/DktbkMZINpuXN987P69oDQ\nCIxml/Yc5IvnW3Fu9RyevX+/qd077bea/m6+fg89+ItRjc7w+ZS5zHviVz7quIlVv5pLpHjaFlLU\nWWgFDUvNAubgQ+J5GYMbCgqr+GacvEh2cMW7aRVf1yGRMX/2uhPXi8wmmQNO/Uir/H00xY8Wscfo\nvXYiDzQ7ip+tMA1dOm2uvvBrgFnzmTLTHBgS3j6Tqa+eoYOPOerQ642mAGSmmn18xedOmAIWnv1Q\nFBj9HGF6Hf5rF1O7+h6W3cy+60LADAq8YFpWL8qs4RuTVH895M9XPAHAtCVPm9Y/s99swvw5SuQO\n2VDClgvelDURGuaEqL40bJJLoZ2GjRdDSOvqTrhTGnNnim/G6FcD8MJaaBzf9/eSiSWCO9a0Fe07\nhX3XGzBNN4fZ5Q8A8MGSvbwwymwiGsEylnOP1fb2Sgk/Hd7B+HbmyqBOuhLyy4WQiOAEJ2nFsEmX\nWDmvsdX2fwutAhXmZ1O12J6RNyL/MlWJNZrAHJzLKMyzztTV+tpScb1mhzxA8LHuxLYRvpqewxP5\na4XZZNLr7gS2rWrA6Jx6PK/7nEhHUUcpYGkkSR+Hoz00j7DILK7YNeGjWcspL9Xw5BAh+PSUUoYN\nHy/fw7MjOpv26djfm89nLmJq914W51FvfhuuTTxm+j2q0RmWpnRGLcvBJsAWQ1wefo6FRIzIYt0v\nQdDyLpxilpJfZu0DqCmfpuq90moNFgL7Bd7nA15kW8YKenkOR29TQVmpFmd9Cc+12kPvdZl09hlZ\n6z00EuKTxeVUd/zqF+CdeJlTRNTZft6+LUyK7oNGMeD3ayQp9x3GUC3nR8Fg9pt1uI+uV99BRTiG\njXy8YjfPDu9CIy5j09adiyfdrCLWvEklDWH2PLF9Pq16TLzh9VTF3buYrDTLgJFR0y8x5aVzDGxg\nLqxpQwmTXrvED280x+fZIFI/jjOtM5avf6XtDp5oeQDv+c/Xerz4ez+j4W8zLJZNanqMeefbVGup\nMq7xaZZeakoZ5meuYOC1eYd5fVIHhjY8z4nfHiC+826rKgx1818wbf2ndTtvAuWKNG3dcvbliBF6\n/Og+JnNDVSEC1ChEAJp6ZHF8iiNv/WIenRqFyLSww6TgxzvdtrH+aO1RMUai2M+r9++xWq5UGEel\nQphUFyKzeJutSUKTeiZiL2OfEOabslIN9p3NpgpjCOeHb1+gOp0GmKN9Nn1gvta/VtTHw6eYH58R\ndZjqZ4rR2aB3f2LoBz8DlXOkPLeAqZ/NpqJCQ+YpPf7HLrDg6VD2PunOl2HzGRty2vRRx8wUzsuA\n4Hweb3GA0IsH+XJSC6tz+uKXmQA0c0tn8iNnyOvohFqYDWUqpXHFlKMnscCVqT2P46IvplHaRma0\nFM/hWSzNf+UIgZr825emZZ0HXcNGb+Dpew+hVskHfHnyXnbSjVad05hbOR9Kean4Bme23slKxxZ0\n9hnJ+sfNxTqnvW52Rk/sJ0a4jbjM5crs8dwcmxsKEYDZ0UJLMagamixZjfN9ZoN6MzcR5utBldDt\ng7/Sptl1CyECsP8Zd9o1uUYmHqQl2zN+mjlf46mWImCjALMGsy5F+CmCmuWicbMcfLzURmjZJkK7\nAVCi2NE7wKxN2dhWsOTbxsz/SGgsT7bcj8dzIZRiS8Jc8eyrChGAxAVi+VtHu/OUh5i24dF3zCWK\njAEFPf1jrYTIqOmXmHe+DaOfj8cShbxOzri8YPZJBjXL5Z1e23GNcuSZiL2sjm+Kw70raeySgaPe\nOqLPmJ1vpKf/f5YOcCdyxwqS7/acoJf/Fb4rmY8+9gRETyYEEXo6GmE2CeMsB4f/yG+9l1psW9aw\nG/c3PWMKJZzXx+xD+bzTBtK13szSrWJIh6M8yecApqq07rZFovYQ4P5EMGsn7sTufE2JYZaaolLt\ndzk6tPa+6CkluacXX2SvEudWomVy1kZTOwddGc99eZSrU1cA8L7D20xscpzzY77i00JzFFF5BdBq\nmOm6M1PtcDwj/BN/lI1j//CfuKv+eQJ/EL6hhRcjuL/JSTqzh8/X7EJXmI0hN4fTbs3RXznJsfOg\nv3zUtP97Qs/hTxJJsU6MDjlDSWIZdsWWOTW/Ht7MxYdEJ6rJvk7LP1ajojFVZfYPyueHbmtwIYe0\n3QnYeKucuesN3joqJh17fLyOT6PN5ipyxD3v3udP06LBaWegQuUd+400zRtkvtvHy+nLZk7s8ebX\nT5uCokGvEcI869BRzuz2IHXCR/QqvFBZmRfejRX73Zq0ApurpayJXcsVQnAij1m8TcboD5hUtTMG\nmiOEz8hGZ7Bp6sSI4HP8MOq4af2VcXdh/8sh02/3qDK+9X6bNgHCLNjTPxadTQXHz/vQrlsqazaZ\nw8BXxTWj1ENPtnd7Chv48WHIL+y5ew5L+i6mnrIH2o6kSBFC68g9swmcLXwVjjFX+X3XGtN+Bo6P\n571jXUmLMud7XGkvqkg75eWjSxKDklm8jYNailYx0OaH33mixX6+ONWRzI8ukzXpfaJ9hWlsVkdh\nDjWazzr5i+VanYGFnwkB9OObZj/jsBZigGObegG9bQX92EjzZKG5fpS9ltkPfM3yX5oQqTvCxbFi\nkOBKNvELcnGbahaucTEuXE9K4mpeW8avjOMV5S3GXPsW/x7FpFYpS+Q4wIfw9pm831/4wXr5C0F5\nJfm/OJi/zRMS71jTljFqa/X7yxj6ohiN9xtz1ZwAVQfh7qm0nphF/grVFMpoxFlfQu8JSayc04jw\n9pmcPVR3NvmGdu/yiusDHNpWd3azEc8XG5PxvhB4QcQSRzCtu6RxfLfZpls1CsfFsZDcAgc8X2hM\nxgeWORpDfy5j9WQxEp3Rch+fnbKsVdV/XDwbf2/IsCWwchT8/NKf5JzQ8dS6/nwf/iMPn52K68QG\nqKUGXFafpV5UMffcdZGobZdY2mkYJfOv8FOM0MoWvrWGTb804C9CaN05nT0/O9NrejZLvrU0/Tk/\n1pe8rzfjRRrpeBPSPIfLZywjuwK88thyeDlhQRP57s+tPDJYzFj4+HWVr3zNH7+tq0pJjoK9poQi\ng1mj02gNtOmabhXZtrnNG+zTduPVSnNh1XIgT354Apc/sjmc5s+W1EaUlWiZEbGPz05GsyV1FTOb\nt+NgWn26353EkXVe5JfZsjZ+LTPbRHIy0890DGN0V23MfWkd63OaWN0XI/oQB8ouFxIQnE9SrHUC\nXgPHHL4Kn88jPM61Q+Z7ofWxpSLVbNqcGnYE+4gMvlzUD5dxAeT+LoTKqOmXaj02gJdbIenZ1iVk\nYpb+RLORD5p+T3z+HEuPdaNgcxodxthzcJE5HLhttzSO7vQmqk8Kfzy+kuC7H671eEY8Z4aS8a45\naKKmCL7+nsfZ6DQV4s2C2MuugHR9MIv3LWDe1FD8epaw+xsf67Lxdi5MDNzJ/AutTeVazMUz/wum\nLevo5luOcvF/Z9q64wUJwL0s5DfG/6N9nBvzNWGLHquzzdSwI/x47p+Hgf5dHnvvJF+/JEwnWZPe\nx33ei/9o+3pzW3NtyvEbtvtwyV6eH9WJ5f3+4N70aRQfNScJzt2zlSmde9PJ9yp7K7PPtw6ZT++1\nlrb3L9ft5IlBwjwyf/8WFo8O5PXI7bSvnN/k7+AfVMDUV8/wxhRzqPbM2Ud4d9o/u8d6mwrKgvtS\n0rUntj+9Ums7Y/hwVWqbBGta2GFm/82w3f+EfvUvsynRMky2bfdUjtZS/ReEGW/PutonT3vv9328\nNM56LpFbzbTXTzP7dUuzpq1dBSV1VIIOvd6fi74ba11fF3/0XsrYrSMZEXyON7cfpkXD+2+8kQX/\nBUES9p9u/Z+jnJM+klvO9DlCfR06OdY0J8ar7YSz2aaJsCM/P8h6ruZIDuFNqkmIPN7iAMOCYrCl\nmFaeKfR22cUgr6PMaLmPsw3D6KPbbrG9nbaMKJ9EOiPU/c1Rb9MnQNSl6tC7atinEPDdEdu/UiVp\nEYDQbngsFSafiOh0Rvxm9u8Y5/QAcNCVEsoFXoywPI8o9tNkldnkM/aJC/QckWiag6Iq638LpB2H\nye7gwpXX37VYd2SRJ489cox0Gz1tna8Q6JTN/AutCHKynFQp/RUDbRCmrlbHr3Ihx5PX1wuzhrGU\nysPhh3jgBWHX9yaVT/ttooXHdR555iShEdkUJmt4Y0oHbCnmpzeECev0ykY8HbEXgCHPpZoy6QFc\nHMUI/MXWu03LOvS+jmKAV51eo99PlpFwC1/7lsie13m1nbhXZQbxeXRhFy9PFscIINGU8PdcK+Hb\nejl6J4fT/IlmL6FcYPrb52jjeY3pL5xkTJ+ay7a0fs08qn843DyCHh1y2vQeGukfsIdDiWYzUyuO\nMy7oT67Fifc0AmGSaclJ6jvm8Fjj7dRrr6JbJ7LFm3Oa6U+dwKaZE1ofs4P58NfRTG9+kGHdL/BY\nc/Hcxz5uGSpdnaqJrU9NOIydtoyR/Q7z6pgKOvok8FLrXQB0ZaepnX1XoR0bs/vPzxaaVI+3K5hV\nWR06utz8jDr6iJDm/vUv8XyrPQxocJGOH4lw+Wci9mLX1pUZLfcxNXA7T1X6x2wpxpcU3J8ItpjQ\nbIDtdrJDihn5yCV2xnox6/1ueJLOQ2FHTGbGUBfxvdxbWferpppdkrq54zWShjs7E99NdAirB/zO\n0A3jqrS0TAa8h6UsYyRjQk7jeXkH3/Jorcf4wOFNLgYOZnm7OWQu/NZi3djHL/DHV03Y2fFNWjaz\nYeS8SLZSe7LXgy+f5ae3hRNxJu/wLrMAeLfDVmYeFGadmqK6/g7nx3xF00WP19lmWNA5VsaFgQYe\nNPzIkP7OrN5YwFxEtFvMwDdptv5VgoilGztRUfgFMQ30hkG/MmDdfRb7s2vnSq+0Q7zWbgdRK6aa\nlh+753vaLDObOTxJp1/ja7zabgdhix4jyDmLuDx3QAVFwd8+l+SQcaxb9zCDGtzF03zCpzxj2t7V\nppicUjvyJ72J0zyRY9KLrezWdKfUoKPkgTexnWOZe1LTaBnA+/0wzsdMYvCCbuwziFH8s3zExzxn\najODT/mMp8m89008fnuVBo45JBTUnHBZNvVN9D9aHjs0IpvWJzeZCmIa8ScJO4q5Qgi9/K+wLbkR\nDYnDs5sDR3eaNZI+AZfZkhRC//qX2JjYmLH8zh+I97mVZwonMswmtof5jgYL2zCrypzsVVl16U9e\nbRzACUSirdHMZ5wjxDgviZtNEROanGBOfDsKqkQL7spbRlfnmoNVqlLwwDs4zplF7uT3cPn5JUAE\nBnx+KpoZnxzns2csE31n8CnhD+qZ+pN4Z6+M+4JGvz/J43xpChWuSsOmucSfd+H4yO9ovfQRHmI2\n14O6syquGaNZxCWvrvjaF5Be7MChtACLbXv4x7I9ORipkdyYO1YjWfmOmKHQa9x2JjU9RiSHqgkR\nMAqRloiRyjJE6GdJPRt+e+hDU12qUZXzVwz0OoaTaymR3kmsKezJ2hh/Shd/ZnXsP74S0TIz9/dk\n2LyOXK4+L3Y1zv1ktoWXt+oBWJaP6MIu8sps8Sep+qYADPE8bPrbwdns4L7751KTEJkWdthqu57D\nhFN0ZZz4CnoNT2Bt2GcM2zjWJEQeCT/EPeuFI7Y8xJudzkM5jvnjz+riwqD74iz2+1TFWrJyYfyG\nIQD42IkRYJtlDzNgnDkaJ5SLKKhEr3iApm2MQgRA4ZPpW0kudGH8wBiWfCvu36Ggx6mHOXmvTCOe\nX9Jd9UwFObfRG1WFt3+8QO+5woFbNR+kqhAx1trS6gz02fEzHvNeIN5g9qEdRJjYHpglnMif8TTN\nOMexdGGiGTbDHPXTdYg4r1aeYg6ZiCWPmNZFVc4WmXxSxxJGM8jBPJpv4pqOxtGJzMoS6zmVg2XV\nyY3kOEdTnTeALUkhuJDDxkTh4xh0nwOTmhzjnuCzFkJkWNA5vucR1i6u3ReyYagP1zCbxSY+L7Qb\nRSeEhXFekuxSe7483ZH0MR9YbD/8s5lW+zQ6savybNBQQOT3GDlwSgxu1z4jjvF6O/O7/hlPm4QI\nQM7doizRPqLp62Ftpm2UdoZxjU+hU1S8ScVu0GRWxTXjseYHOEVLLqY7sT4hlMQCF1wnmZMU6zvm\nEKOv3Wz4j7nNa23dsRpJRKdHObnXi9l7djKts7Ddh6xqw+W7j1m1D1gaSdJIc0frPtqPomUJtc6s\n5jqxATnzExg+5RIr5oZQVyn46qNaqHlmvpp45K1TfPdKy8p5OpQ6j1N9JjhbuwrUMgOllctOjvrO\n3Ln5hUHKORYPXMLo9aNMo1Et5Rw6t4j2YWPYO/xnOq6bBsCqHgt5Ja8vHrG57E9rQIVWg++KTiQM\nsp7qOYRLxBFE3waxbExuhlphOSfHWM0S/jCIGRhDXTO4nO9ucngb/RN+DQoo692EjHlJfN1zA4/9\nNQCA2Hs/tyi8aNRIDhsWE6kRo3y9pgIFtdL3YdY4NVTwMm+T/MpIfnqrOTq9wRSVZ2tfzqttdzFr\nT08ef+8kX73U0uJeN47rw6Ugc9KjkZgxX9PsBn606lSdL0RcsxBmVWuvoYFuvvHsvGYZ/murKafE\noKNj3xQObvapcaqCGqnXvMbqujXNYePhU2xKStRrKigzWL6ntvblotI0oGnSDcOFnbzVYTuvHOxO\n9fdTQwXbslbTw3047bK6c8RdmNKM88580XM9L+7sYzGfjY4ynv32JO9Pr+4XU7GxqWDx2Y0Ma2wu\ncxPYJI/Ey47YUIFuSAMKNqaiFhtwjHCg4GTN85toFEO1PJ7/gkbS8sbt/tsop6RGcstJv2ZHoFM2\n234Xoy73J4KthIhxPmyjEGlSOWta1uIUSyHiWo8Hmx3Fsb83L7fdQdP1+1ActSRfD6T6x2OvLTPN\nIwJwFOtcE6MQMdqKI6LT6Yilv8b7/TC+e6UlBEXR2i3FdJz7n43h4cFHsdMKzcOpMo9kYhNzpdpG\nXKakWEu7PuZS5G22mTPtm/gKf8Do9aJD7/2CyLh2mhzM5392pQIdUSumopYYCHvKk6Ebx5FzSkua\now1DHopn6JRY7v1kFdMrbf9Vi/9VNPPB5ckm2GnLeeoFs2/ASH59c97FFZt6NInIYfKL5wgOz8EG\n4fNISXAkulIL3HXCbM6bO0xoScZrLy4XHdrGKHNp9zKD1tQ5KlXefgNa9hHN7wd7AKJK7NOt99HF\nL56SIh0bGvfnvTVZxH1vS/VneiloC/bRZh+GsRTM9+27EN7esnS/UXuxbW05Ra8Rp0nBzJhpDptW\n0eBrX0DDKj4nN0MW+xzMtpLnw7bSb8xVSgw6Gjplc3GzDgMa/IOF+uKO9UydgElTbFNqLQTbcgR9\npHXEYWmWuHa3R4IoM2ixtRcZ970QWp1RiAAYLuwkiv2sH9iDmgY5BrQs/0Fk6umizYVMjfP7zHKZ\nbBIij1S+S+XohRAJbGc6T4HCsOiLDBvwnsUxrl5wZsrweDZ+tJj8VSmoxUIwG4WIbw3FTHWNxWRf\njV1qnzX0H3Obh//esYIk66qO5AJnPkr4DT2llMy9wF0BlqMyN7JZfGA9AUsjsaHEFDLYQXeUiBNR\njNYtx4YSfor4lgUxzSnYmMYzEfsoTs1gRsGHtLpykll6Ub7DWJOoqEJPcowDdhSjo4xXEjOZ8Y4Q\nYDrKMDrZFQzsT20AqJzc58V+OpockwC5Lx6jPxsg7gBJ46N4Ry9Kh/zycTNyAh1Ngs5QXsZg1vJC\nhBjtOZNL8/vgST7Hb4SHadKkwE0d0SOEjvOpOMLc0nCoFEK+S67gpC/h9X6/8MuzIuP9r7vm8fWK\n7cw5/x4TmI+/Qx4Fl0pZvqQ7U2N388k2b1Mtq7XxofywZisP8BNxMS5svPoSGluVEXGn0SkVFuXa\nz348EluK6aA7xjuub+Jw7AofVKwjMcYJm4b2LOixjE8c32BR/DfUc8hDfbs9zyDucdHo7wEortBh\nry3DTSc6iejl5o7UTluGVjGwteMHON8jhGf7vB50ZzszMwso2JjG1jSRF/TF8fbsTmmIq00xI8tT\neHT59yzu+YfpGT2PMOesvPgnLY+IkvyDWUvcS9/ThqPMSt5Ck1BRfsN4b+dUJjv2qFKi40m92Yfm\n2N+fv743m5S0OgP2RWn4dRDhs93rxZGnuFJxOQ/7zh7YUkzIx4opbD2hyIUcxZ3m7TJYeWwNTvoS\nvun9F/cUNGbqDic0irjXP+/dwoRrh2l6IIoTGT48o/9KPHuXUjRUMG/kQUZnmU1K58Z8DUBBmQ19\n2YT257Mc7PkmJUVadJRxUh+JlnLWJ65Gb1vBgYzFONiVcICOpJQFACqr24rnNPUlce2eL4fy5Y6l\n2GnLOBFjHtQ47BJh6p1XzQPgk6j1LEgU5tJ151ewp2AZ/tc2EqGc5pJe5J8EOmWjTyzBOX4rfUcl\nYEMJA0bFY6cp5ujKPHzuLiOMs8Tf/QZ6TQWRHlcZy+8UqjboFKEVByyJRKsYUC9moWCgnoN0uv9d\n7ljTVn+i2Ec0ASRR3ymPzflRdECYYg4SZWo7LuQUly8XcpAoGrtkkJjrQH824hwazMUgX4o2X6e+\nWzHplQPG47TGlRyCieV6p3YUNGtA+txrPNDsKIdS/TmZ6UcHDlCODgc/b3aniA5gevgBVpxtQAMS\nKo+vYtfeneJD2Qz3PkBSGiQRwDX8MaAhUnuYhl4V6EZ5sONrJ0Y2v8rqM354kU7DwT6sWB9smoQo\niFjcyOY4oqxEMFfo1iQXZ30JO8/YcZJW/Bj6JQcbdENNKOFMo0D2baxHpwHXKN9wFY/hXmxYEcL6\nzl/g+owX7z4VSdeoPbywZAqPNT/AwTNQ7x4X/lrmzw87trPnrZ7M2wIBJNE0SEGnGMhNy+NkRXM0\nPgrvTFjG9281xX+MC2X7tOxPrU9GsQMtOEVxg2jsE/biX9+B/PxsQvra43I2n81JIXQbncCVP12J\n8LhOcncvEr/PpOGUTpz74RBl7gHos5LQU4ZOC1pvP/yedWHJs+6cXTuH4a+MwOnYZa7jS4pSj4fD\nj6ACB1PrEzy6kD3f2PMAc/iJBzmycDmhv79N+NrVFEeHYLfvMiOjcrma78LBM0KLLEfPg82OcCHH\nE59BJWjWZbP4WpTpXpe6B9DeOxmXdhXkHNGSnlrCuuwoGnGZK4Tg4e1OZloWjblI+8bFXFPL2X65\nDfiE0iH1Vzo0h6/PRNHQKRvf/POkODWjvXcSu8uCyHQJJuDsfjLwpNfwJI5s8qe3TwzzY6OY1OgA\n865E4WOfj7ZlU7pmbGTT5QB6jr3Oij9EzpM7mfS4N5WUDFf2bRRCy2gGdNEXM6HJCXbFuODlZ8tW\nZQQ9DSv4KzkYb1Jp6JPG4dTmuD0YiPv5y7jvOkk6Xmybu57GUx6mHYc5QiSRHCKJAOqTiMvjg9i6\nOhj/+JUkE0AAiSQTQHsOmr61oZ8WsPppy/l7pn95ngtPXMXew4WG9cT9aMNRuo+q4PMlYpDSiuPY\n9K7Hia1ujIhSua/8S4YcESVXbEIdeeL+nYxIPsn3ZzqzZpcX3504xIIhjYhPKCHAuQA3b0d2VQTT\nRRvHkivNGdnoDEuvNGdW723E+/lxeKFCDItv3rR16yLDaz/uYZlHcktRFEXV6V+pdZIbI8ZaS/8E\nraeeioy/Pye0m1cx2enWsxP+bQbMhA3vCstBDY9SUdQbzrYIoPXQU5FZ83krthrUEgO0Hob7ud/J\nKhHlTjSuOpSCUjGPehWfAlSWqze4Q3kxzm6l5GXboHHXo8spssjN0LjqMOSUm+z7Vfmn84NrvWyo\nSP8nM9tZRuXVVEfKiOKoRS2oYY71avOm11br7L9N9ftdFb1/Q8qSLUuIaNz1GLL+6VzlNVHLi2bj\nAKW1zKmu1VvNIW9c7u6RR1aaHVpvm1pnJazqdzHyx4mNjG1lLt6o0agYDNbvuYtHCbmZ1tGMLu6l\n5GbVUmtL0YBOhTIVdHZQ/pIUJDfgjjVt3UiIACYh0sZTlGxo5FyzrRlEZVfAJESMpowb8Z8KEWNO\nhglVRI/Za8uI7GmOoze+Rx9ECdOLfS0zJlYXIvWMk0HVC2dcmEgEGxn9MY+EC39RUKgfhpxyKso1\nPNFiv+l+GieRyi61h3LhK1C7Ca3LkFVGg3Dhb3m0Mm/BkCPOp7oQ6R1wxUqIVI04q4nm6dY+l1rb\nts+gut3eKES+7fIn4e0z+bqzKO+uUwz07B+PrbaGe2co56mPjhMcLpI0vfKSrdtUpYHQCu0i3axW\nPfjyWVOZHvfpQaK5Yw7YW7et6/31yzlptawmITLsQcsoKg9q9wkYZ4N0dK7lva5NiEDNQgToPiTO\ndM+feXV/jW1A+F18Prac1+e59Y9Y/DYYFFqOsi4Nn5tpazGR3IOvCPN1bpaN6V5boRqEEAHTOyyp\nm2U8bZYAACAASURBVDtWkAQsFUOEMfxBu+7maUxDI8xOTV3l/Op+lbbScHdhx00Y/yk/7tjGF53W\n49dQdIz2OtF28+mVjA05hYd9KeMrE5xcJ9SHbjWXgVges87kgAURCQNiNC5Que9p62lIe2u281Kb\nXWyY09dUCv6v+4YL+28P67LYLxwQEz7t6PezadnTnxwnsNKJu2/YTzQlhh+2/4Vir+FaoTPfd11L\n4AJXfjOIekZLv2vM+mQRMjrRQeRADN3TgAHr08DVn3UJa0gpFI7KqrPS5a9OMf3t7i0+TO9noYW7\nWeA1xpwIB7A1qRGB2zvRozIE2fmeenyzwewjevKjEySM/9Rim/n3WAYkaFx0tOUIGy6tMi2b/NI5\nbLQVnMkcWuUeixIxRgYGXuTsIQ/uaizue7mqITr2Cucnfm2x/0f4lrsmxvL5c635yknULbuKOZLK\n3yHX9PfJT8TMg889J9oVHza/Z1sGi3pZP70dzuUIUS79k7Of40sKCQWubN/6I3iY92ujKTdNKzuD\nT+nsd5WPlolcqLZeyejKhVBb8tZuU3LehkG/0r+BuePcdngZzdqIoI/nvxKDkkw8Cah00O8b9hPO\no/1ZcHAzCeM/5amW+xl0Xxx6W3HPXNwtBcrSs6LA5/kxX/Fw+CEaJ/Q1nV91HF3K0GhUdqwKwPt+\nUdmgxzDr0PWqz9exr49FmHbCi1d44tMLzD8gAgVcyMEnTAQwfNFpvcX2/oHOpu1+eqs5/Rtc4q8D\nS2lunFa6ssbcLz1FSkBXv3jT/RzFYqvz+o+Q4b+3H9VLpPwnjAg+x/JYc+RM1TLyVenPBjby/9h7\n78Aoq62N9zeTTCa994Q0CCEEkhAIEAi99yYgSFVRD2LBrigCoqIoVZEqTTrSey+hl3QgJKT3Xidl\nkpn7x87MZAgcv3OO33fvPbr+gcy73zJ79rtXe9azBv9H9/oj6eSQxd2niqk00hT2a0chRdg/c9w4\n7wfcTTElDa9mx6wopQxhFbcmgcf46R0PJlKbf2lFIknoEwt9++lhPv12lN5n3iSTQnNubQ1/WEiv\nfOIvW1KLMaYWSuQVFVRhhodlJUnldvhaFZFYZkcvl1QefTQM7yWnuJmnb5E+DaXViAQVfiGlPLpv\nA0iY3jqKrU06XD5Ng7K2xzE2PuqgnWNNqKUdscTxfFznH1GVa/ISGhnp+agZd9u/Kg7GVdq2sZp8\njPZ+jb9j09/zn4ktRRRjp/eZIUotq3JTeRYU+N+VplT3/4rYUIwzuTzk3+tKChA+LJuc4wpycaYK\nTf3WnwD/fXbd5/+qSG7+Hdr6P5N9A4TFcWCgYPw9kqyjDem+ViykS0f3aD9bYLmS1iRwd+PLABh6\nmDD3hyhMnRq0509ohLseST7OaQYz5KVULG2b9wKxmyc23HCuNjvW1Fq2eceHw8knCOO6FmHi87AP\nHwVH4BPXh6RRYeyOv4jd5+J6VtN1G2pNg4yvQi/gYFxFEfZ4XtM1HLK2r8WphQhJ3Nn0Kml48cu5\nSwwbqitUOznkN+2mcyT5OGntdMHeX3sfwi+4hDFb6+hon41JNxvkobZ8vVPfM/j021Es3HJLy6oM\nkNenMz4BZTivE3DfliTh0bqCVAQ1/v3LjkxgLyM9H6Ec9jYl2FKHnKRyO07eP4TXQAXXR2/ico4X\neXPjuZnXAq87PfXua2yhpgP38Y7prf3so+AIDIzUnPDbjkEjkm7r42AmvfNY25v9wOOT2vG2H7Wi\nh0sa/d2SOZJ8nFfmPWBmtWBArro/R0thE7FLNJta3MRqNnFsoD9nuTxyM33GCM/q/eWRJDfeR6NE\nVp8UiLojaW34bO1dfAJ0XGbzD+dz9rLoGvn9PgHL/s5hJVgL9Nyufvvp5pSBS4jo9VLu70ovl1QC\nbXORJL8GFo6s73kUb/8y6gf6YkdhMyWSPGklHheE99fCrIwBnMHBVUExdrzMJiY2gW9bGevCVLPm\nx4OhMJ52JAmEl09cHy39j+baGrZrjUx+NwGk0DK5H48mCrSYxqMBnqlEvO6K33bbbRGi/S1ZvDOe\nEbr13GdoEA9NwlgWJkKxH6yI5OywbRAwFJmvGcmTVtLhhFCsRwfvZH3Poyw7HNH0NkQcd6UOI2ow\n5re+v+t1Mv2P5L8c/muwYMGC/9s7/n9AFi5cuMDBOBRFvRH3k+WUYEt6Kzsyn1igumNOfIZwhYuk\nrVEm5KO8qyK22AkP81IaBnhQ6ulHwKZzBPoXEPfIEUW5BEVbbyofVCNN68PpG9XUY8iDQi9yYw2R\nKDx5/2EqCQdFO1WvNuUoquWYDnWhKjcMu4YUbUhIigo1EtQSKfJ2FjTk11Jzq5TdK31RIqMSC0BC\nSUQQmcoCXuifS8SaethTRmyaLfU5tThbyClLFwpCblDPg0w5HVSRJKlbElJynTxrTyaa3KaozITS\nEjl1KkO+KIsgw8uWok01PPAzRZmuoMdvVnz1TRssvn6Hugu3mNjlAcWJvUhKLmfE6CekFVqz5FQE\n/+geTn0re9pVPUZm5kXWPgWth3YiKc8GFCJ8Ir2txKniERJTC7z71TFeFoN5VRUxibYo06ppwIDa\nCiOk3RypTxdQ19A9IdzcI0Xmn4OvZTphVtk8yrejtFhO3H071kR1ol+PBJ6kCubjlcGLOXQiSPs7\nW4x3Q55Rg3fWPeRZdRTWmPEkV0al2oKCGlNizAYg96yhIa8WSWI9AW8ls/tgRwxyBvNY1sCgfgnE\nrFVx7YExyY5DmDb3Kmc2D+Z+gjEFKgdK16WhRAYv+HF/rRFZCksq643o7ZpKiY0pb1yt4M4KCcm1\nrjyIt6e0zoRhU9OY8u0I3MebUhIvjIKkHXWYmRtSXmdM+rE6bNRqyjt7oUytxiipnNXbR1NdXsHZ\nxvaweQpTAl3LKZUZkldihu/4Ymzv3udRuROdSu9g52xNtMKGAYU3iL5pwHmvbhj6WSK7m4myxoia\nBhnmw534cdoRTl7w4WalFekpVnR+EMe9Sleq6kzIrbAHUxu83CDB15/8J8KwlVjKUFaL4kdVfAPZ\ndWZ4+ZaTGmtGcrwVoe7WPDpf1LhOYVVcF+T9Q2h4oOuHI3lcT77CDPtL9/n9vC35ODGo8jhHooXZ\nbuRv3gw0YTwkjMo9cZwrDqdfSDzxZyzoNFJCV7M0ru+XIaOOITOSmbAvi7srZMQWOyGJUpL7SR8i\n1zxmuHsCD0f3oGpXLAoXBx7IbSlLk/HD3kmgKAaHVnR8s4zA9EQel9vj8JIT1Vm13DGbSn7xaRYs\nWLDwP9lvFvy/0LN9YQb/0XP/K/KX9Uje2Siw7E9oxbeHM7UwyKQm/Z8UR4QltiNRWM25lSYcO+CD\nq8ETZgfcIVSdCTJjYm7Y03BDWJzON7+gBFskPlZEZn0AQCdJBOtaGGuL01IfWVJXBZaUQ8wRIgtd\ntP1GtNXIKjW1sbre6x6tK/AiFR8/Ya3Oiw7lBcMYwjpcwTi3mD2P2jJpgEhYpkXociS1DYa0IomT\nKhGzfndpNJbRGcgS7zH0s0zMnMVm9vN5Sx6eUjE74A4tlY+pLDNifPZmjgzaRcU8YZVlrZERUVzE\nMI4xtfI+wb8ZM6/4C2woISsG7lgFceN6LdNax2B+bQ0UimSuMzlcyPamDCvoZEVmhAlbR07nntKZ\n5c7CI3Qlm7I6Y6qv6gANHb/+hroB3uTtKCLqmgMH43yZ820Mx/d589qbsQS6FaB20EFGY98UuZiW\nt4R1XrwjF3lpFtcOOPOwVCibXFwwpAFJXyltyi9QGyPyGOkSa85OE17jzv1PqI0uZ+YnDzCwNyJG\n3Z7ImCKS06x5r+sm4pW60Ek3k2hWvfcbvd8V9zbNT2RHYiCZTyxY4OlMLIFcL/Ci/WChUD+f0pUK\npZzkPbqNctngu7h1E8rzxZ+KiHf0RX1H5DZecC+gbdVFNvY9qc3ZJXbsQa69IQovZ15a/YSko7aE\nfqfA3ayMud0fc9bBn7IiOQeyRbhRcbmIEzVL8GxTLkAQQOWxPJTHxfXC5tRSeSSPfH8LqitlZNIC\nC8pBUcLBVH9mFh9n49ULAJhUKZj1RTwO3tUi1Fenxv1RNF57BYnmmc+iGNYmh93RwitQI6F2/zGa\nStuXypFI4XG0DV/EitzIK1t1jARtHwpv49MO4t/xU+LJHbObXlyi4vccPFpXMGVOHP5n79MnTORI\nlBiRtKGEJcGO2vfVsSqWTRPF+p7lepORbidJj7DEwyiTaydc+CLkCt//slXctCCJIa1vcjqzFYFO\nJeyqWMEQi8e8//3fOZL/ifylcyTtbfOIlXSFIsGJ5BdcgvKJmuSKf95DpAXpvJxgwEI/Nz5cdZ9O\nR56QMsuNTyYKBl5X70qyn9Er4l+Vcd4P+D1FbFoaKuym0mtkFokvDCd7WqQeRLJFqwoykoRF6Lw+\niNzXolnb4yhvXBWtUDVY/4698rn3FA25i2kFOQoLvc88xshJP1hLd6d0Kn26EX1D18t79uJYRl2P\nYvSJcbQ0ySW32oJCmve79g0sJTFGF1LpTgRR/cdQda5AL2bvTgaZCMtbk19a2e0khwxbceuKK6Eu\nBdwqc8fWqYbsFPNn5lrMZbVUKuVMNdnD9uqJIpkafYinZWe//UzWm1N9OPCOvvt56YI4Hmiby7yQ\nq0w8N17vGsFE8lDaHjdVmjYfMYxjHGc4dsYKimqa9+74I7GmhFEf5bH1e5Evafp7Pkumj4lj60HB\nEeZjl01ykSsAk4fexK6HKas/fXaXxq6OGY1Fr0I8SKPGxE6v6dPTIjeop7ZBrLNguxyiilzw8K0g\nPfHZz/e8dtVP56ECDOKJbwjQGyMPtqQ2qpzBLZL44H4c/R1G6x1f3/MoyS+6aulSPM1LkVUW6OXo\nLCjnFcfT1OYXcLXzRHZ47GXb4yCUk83gh8esKmzye9p68FXLLXxxR7/985+SI+n1x+P+bJFc/jtH\n8r8ucy02U1VcSUSIrpXnxfHb9JSI1FK8MPsH7GUCe1ja9QwAdlaVPPYTce2lb4cw8dx4rRKRSRuw\nTMngPX7kNf+7TDPX5VyaSswLv2j///p7Onhi006IQomIvzVKREPb4hfTnUdnrcieFkkQUairheX1\nMpvo0YTIr+6tm4xzPcUbV0doW4neoxNT2M47tjoUlMRIrLdeimOMchee2NwfBQlen3u7wNSWWn9j\nFi0QVdgfWm5g1YkrTEiL5PWrw+ngVEhJtRHn5h/i1MydbOx1mMsjNzOVbWyKOE/nmGO06yLgpd/0\n2M4I86tE8C5+PNKL2WuUCECMVw/GesRQG30P82wjFDJzZvhFYa2u5othuzCUNDCaQ7SxFh7Y9Y9E\nJ8tKpZyvgk9x0GgMAJ890MXRl3Q5hwH1+H/swJTzgmwy6oW1dOIObyAq4+XtxKY45YJuA/QfWcSn\n2QP5koVaqparI38lig78cuUyPXyEJ9WTy/QxvcdLZkdYdPgOo7weAYIY8i1WMedbgeTbsPGs9tqx\n43WV7RPZjSH1WiUSIEtkatIqHHrpF+uFOghL3oVsrRIBqCqSYi6rJdQhi8wad1Z/GshgTtK/Uyqj\nvQSlvQ9PODBwNxX5ulzM0cE7ScdTq0SM/MwJpjnvXL2VCS8vysDCuk6LYuxJMvXvfKU37nr1fhb2\nv6RVIhKpGjMEIqw3F1EjYeJbiZTOF+2R4xt0Xl4YIhdUGyW8xVMZrbRK5OKILYx97QlBbbOwrMrE\ncKXwwi0ox7oylV/eEWtcQ2c0jW3woS8vDWxA8qiQxwtasjY1lFWfBGmVSIceBbR3KOa7rzfzxZ2+\nmHS1wdSwjs4OzyZB/Vuay19WkUjrBDJj8tlRWiil6zxBmTHCRLjxqvJ6+rim8PbZ7nTvZkle40vW\nt28R+W5d6Wgvagb62D/CB9FTRCpXa1lTz2S04lqlPsIJoJ1tHuP29yPM8hHj2M/NZbrMmM5K0ygU\n8bdmQ1oz4BIAycFXkHoLRFA0wcgbgTRX6cHJJB2Cq6xWRkS2QCQ9pK0ooAMODnwPN2WVdlw/BwEN\n3c0k6hrLJTQU3q+HFIOiGOWjcqaNGAjA0vJZtFqdwfQNPXExreR6ngdZuPPR+h5cO1nHq5dH0evI\nTJ449WZheCtiwwYTd0sggLKvlnKo3WQ6nJtHBc+2ZHf1288Ak3SOqDqzlQmowtQ42ZQz89Jocqst\nWBHxAv08Mqh392N98FaCbHNZ+b2uzsPQV46q8etFu4zUfv7jrUAkUuhmeQ0VEsb7xNOij4IuLavI\n8RKdESvDPmyceR3g4UDSNAwe5LGQL7Wd+draCAV2YJIbZ1UCweceVIdtfzN2VI3knUHdiCwUrLvu\n5uX82v8rivPEubaHBOTW1bSc9vtma++zhxf15qTQ0IXfGYdtmfACHYzFl0qpsMbOWEHpU4nzPJwJ\nUYrNNeGGOBZLe+qz1VoW52RaMvbMi5g42OCNCD+ujNXBika5RiHzNEFubqL9LGyQqKVSVTVguCuf\nilIjvAzFM/2W1Zudh8VWYj5cdPqcYdKeCn+h/Dxbl9NrhKDCB0htIzyI2+ecsF70IW2tCxjuqYsp\nV7QUxsRUW13bZE2fmVlHu3N+vR1eigpevPcPbleJosRqTLB1teLISlGI6WFeTrhzGldk/flpeVde\nqn8TZ+MGCufF4v2BProv8qoDsaWuVG0Q70aHlBjs6nNJrvhjZNv/WP4Obf33iUQiUfsFv01ClM0/\nHWfby4ziy1XND8iMQfnsQqU1Zy4xe2Dvf+l53MzKyap6Nonf8yQq4TeC/ab88cDnSMt2paRXuKBM\nq252zMaompI6E2Q+piiTFZjOnoRizS5+DDsNb5vy/qQeLNx6izWlr/APy19ZMFOgctqGFtFQLyUh\nUsxra6vC5i1NgUVbbzF/epdmnz8tLp5V5KSZ8eOpWN4frA+zHTchkd/3+jJv3V2+fl0gyQJtc/Xa\n2mqqsDdcvsCsXrpwhYGkHlsXJQXZJnrXbBNSzKP7Oo+0KSvApLcfs2tVa16am6DtM/4sCecqCcYh\nWghuzxFZXDn6bGi2RtpaF/CgVBcO1KvkNpRDvT7i73lQ86YiMTVArRBeqnvLSjKf/GuhVnk7C2rj\nKp55zLCFCfUZ+usmZ/5yXBbNfeb4fyYd7HOILHTBr0OJdt1oxNFdQX7m/zw0aGVbS5nPdLi7GxDV\n/F4uhSQ/0PWE8TkUTPLoP+4Kqi9/Qmir37979r8vkvN/h7b+18XmaxEOsPfvQG8u8t6yKF5fEKc3\nRqNEPmtClgiAQyueJxolMoYDzOge/dxxGAgXYgJ7cKx6ToUt8Ew6CuBbP0Nm+onQQ9+xmUxmBwAv\nsI+eI/Rd8lBu47pdsAxv7XMQgLeKt7B1w3meJb0DhFU3ZaKoYn95sngxk61VLJwmOI4GH4rB/53V\nWKwvoQ8X6OKdhSxZyfuz7/LWtzH04xwT5Ed58+tY8B+od/07i+v40GEH36xsfn+7T3XxbY+t7ejt\nmsKOb50I7ZunNy5yrxQ7uYKz3+ks6ddNtmv/P/a1J5iYiWTyucEleueihiHmCRwdLObs6OCdtCeG\nHxwbLeBQ0ZdGaiDm3oB6Sozs+X7/Ndqm5jxzzroPFd5pcICcyhoJXQeK5LuoVWkuIT1FiNIk3JaR\n36RrP5/Ibj06kLbBOdB2kN65lfVyevjqzvm6s24e21gX0NE+G1tFHh84iO+X+cSc1Y1V+hpxXhPI\njI913Rs39Dyid7w2roJB7Z9iT2iU4IwryNE3pGyLxLuigXj/eDCi2XlPy7BpqczsKNbWwfUHdd8B\n8VyjLJp3l9zR93esX/Nsth7MqKSTSRYk66DnqhIlH9ldoXeHPEzMlZh0s2HRD7qWDT25jLdRNq5k\n0dqqUNvjxy/4qfXyZ8jfHsl/nzQtSGwZUMaT+Gd3sdN0V2tqWRuiRIaSFsG1PI6ywa9DCfmRairl\nVihrDZ7Jz+VkUoltQB0P7/7zJD40JiGNraCmvNFTscCScsrRf8auTplkV5mTHv694Nr6A+nimsmt\nbHcMjRqwsFJSUmD8TEu1dXAJ6hQVmZWWOLSsIf2xBbZyBcW1pvhZFWIUMoLYizdwJI9qaxuMvC2w\nrCkg5aEllkY1NMgNqKqQ0dYmnwclukS+uVUdXtIS4kpE6MPaqJoW5uXEFou/TVBQjWmzZ3ncxGsM\nccvjfpYYb0oVCpm5lsrCwEmOY14KObjqLmAgwd5RQWGOzvPwMC8lvdKakDa5PLRqQ/Ut/ZbAAO26\nFBF3yw6/mmEkGIscl71LNS6eVcTetMeVLLIRXoaXRQn2xtVkm1uK5L9FCSmNDbia9nz/Z5xqQba5\npGCj5YR6upDRiFrqzN0IkD0gvsRRj8/LiFpaeyqIK2oNlQWYmivxMCzlUakDK45d5d3hop1woG0e\nMcVOIJWBSomJgZJqYyeo0qf9kciluLmXkflEF17zsSjW5g67uGRyK8cdrFxxtUkkO1U/d9PZIZPb\nBe7P/J76og9scCOTLHTnNZ3j54mPRTFGvhIe3bfRKz41pQoF4rk6uOeTlmmAXZABtdUG5Bm7ocyo\nxse9gJLYer0CXa825aQ+elZk4E/wSAb98bg/WySn//ZI/s/EN/66XmdBj9Y6dz4tQSyqpuGZemQs\n6XZZu8H5R16iBFuG1x5m6gePtErkclaT4rtqc9rd1e/5oKFo11i/Gjk98jeoKUeCiqAxxYAEL1I5\nPWy73ribee6EOWViZNygf71G0SSENdIiW1hq9fVGrJ4nLNhnhTtSosxILLOjukFG+mOxmRQ3dsOb\n7BvLsBcETUg+TlSUGvHyzBukZPsRYJOPaV2Jtt3qTD8RPuhgn0OATT5Kb3utEvmp+wn2/LSHrGKd\n2RTirEnc6vqE/+x2FIAtjV6URokAYqNQqhnaVliPbzpcJrxJIRyArKFWT4kADHQXOYH7j5z1lEgg\n0aw5cwlAm8t568KHdOA+k9hJbXhLHt4UyrygEZW29MA1UitsuFvgSnmAQGylVOgUn/12XSFeaaEx\n9i7Nw4gA0cXOesSC9hJ9zisf63L8/R4T36iYm5JC1iFHaQvGY/uypPM5TCuFEgE4+L2XdlxSna3o\n86ESXlp1g4x5rQWSTQOz9SYZda1KT4kAjPLSUfTcymnc7MuymykR4NlKxO1Z1f8Sdn+t84IGSC/o\nHc3GTduDBGDVfv3jAMkVtkz9QOQONUpkNAe1SgQgMtOR2SHxtIm+Ao+LqY0pR1WiJCnWWk+JDOHE\nc5TInyT/5QWJf1lFkvjpUjraZ/NqeDbZuOFvXUDmZytJf2yhTb63IJ1NvQ6zsNNFvXN/v27K9r6C\nl+cQY+g/MImDjOXEdsGH1MPkPofdMunIXd6QbwHQ68M9YU4iikaL02ORSNKHO4tw0sAjUwHR0OjE\nb16AmhiCSH2/+Qv6Tefz1B36joET0xldL7itQrtl81a7W9qEsIW0CluKmDSwMXGsamDKu8NY6riC\nBZtv801jFfqlvqt49fN4lIjnklHH6wtFqO/CccETFdK6BN4UyLUv7Dfw9nfReO/NYYXRu8i91UhQ\n842RqH/6/KaoRJ7iG4PSU4bVZPH8rUiks2MWFRsVzF6fTFB3kbC+1kinP26leE77+a3Zc7yWF91u\n8fqNkQx0T9ISQnrL09hwKgUDRxPwyef2wB84WBvAuhm61rYApsbiWmucdc2OpBIVBpL6RsJC4c2Y\n9rRjZutIbViy+HvRN2PO0N5EEkKGc3eml52hHhnf3M9E1rhPvdxYFX16wWkqj4lQy3uB17k0Ygtf\ne2yhZu517X3DuUphjgmd++eyve8B3CY+O2cRYJNPmlLXj6S3YyLrXznJw3vCI9AAPI7tEcr1hxUn\nSYi0oWbbHj653Z9WjjX0ckykY4scPpyq4y8bHJpI9DXdxjniuCPqEWJ+zmQJxamBUds61XAs9RjO\njU2flseG8Xsj84ODeRWT3hGJ8e9H60JqqWP0697ONDF8+mSthK7TtX+PnCl+pytqb+1n84elav//\nqo+YN41CHeP9EBeZmN8zuYd594coTg/YxJ7VR/D9VQdFb0kSiiRdnibE4SHOBoXItnsyOjQBCWpu\nvL+FNjwkpHEevWTi39Mugqni5/DjWFjX0ck2HV9rfQblv+X58pdVJENPzKK6vJq0Sa60s8njYakD\nvQ7PAOBGI2dTBh78HB+qB8kFeEBb0l7WhVBirjoT0LmIojxh/ar7OnPNcSIAm5RTm9072bITXpI0\nfCyKyRgr8hARuZ5PjdLdc3rrKK73bb6oZ98UCeszezzod0Ykme9cd2V3sa5uoEJlxvuBN3j7jCjS\n06B+Psx/l3W8xmeTwwBwc4SDi3UWvxIj1n0p8khR6UIJ/Lazjsxeohblu8JprPo4iKyHORz9bikZ\ntKAEG7YwQ3uNwZxk4z1fHkfZEPTRCoLtckjCl5xCuFMXSIhDDtHXHDBr9Ka29D7EirUC0VO46DE7\nenxMir8ntTUGRBU5U6AQ85utdOPYXjUWKuFR9Cz7moxEC5JznlrOjbrzEx9d6M+GUiSGUg5t9NH+\nroorRURLdBXx734kLHrN8YjacM4+EJ7GZ938UVTp82d9uUYHXV0W043B+e8yL32G3pgIRIjp9jln\npl4YS9BhUaTX2yVVb1x8iaMeC6/K34QPtvcFK7He7hWKfxfPDibYLocP3h2id/79fEcu5/tSZGbG\n5wd1dDZvLb6tN+7osHxcjgsv8F5+W3b0/V13UA3DvYYzZLTu2VLeEGtAJZeya2VrAD46JDLI433i\nOTKrj971m74zF+nLum9085G+Wfxuaz7XeSr+Z3Q93jcmCyj97UZOxYMp/ux1fh+AqunVbLw8iEHF\nZ7i70Y5F5ToQRSt3yJyky+vcL/Ant8GeNu/cZtMj0X734T0bHJxN+SpAeLupSlcsbWtR5Yic1psR\nw6goNaIWOSUd/jPes7+S/GUVSWK0Na4O4Lsjhfd8BaY/UyYUSLCdWFQ+POF+oSv7k/VJ4NROoOKj\ntgAAIABJREFU5nw+RZfkVVcriL8trLpw5zSij5tzK9+dwDBZMyI7KQ3c/aaMVLUnyRW2qKtVz6Hv\n1oU2tz4O1muLCzCJnXT3FmGdwSu9+OUb3UupSRID2BpVMS9muDb+rEETeZCGe5OQ3oyLo59L6LjW\nTDD9jnpFzuHrIhku7exEB7scPKcGcP77IFTGEjrY5dBzdJlI9lLMuMtyHtYJK7fQvj2ZRSL8EFFr\nQvlYK777WYR+NPmAGZdGY56nC/943LhDobEXEhMpgbZ5NEhFjkEigeunXCirMOHEpe7U3BLz8F6M\nfrFgpUpcV22sCwV997A/9UoJ/d2eIG0SPfb5rE4L4X7UT5BsapiYKcmgINMY0z52tJanas+x2/ox\nADH+wbibNdLIU0BNY8hMblCPq+mzkU/3JGKTv5TjhTvCA+7qmEmQXa4eUeKVy+48KrGHMmE5+3Uo\noZNDFg9UbsSoPGhvq0s6d7DPwchKgpVdLWYWSi2UPMgul6lTRR1S05Dnyrr+2v9/X6OrmCvON2YM\nBzh9WMfrsWqsWD8VJbq59Gus1bha76Vtj6tpYTDg+DRatBLfXeZtyut9dYpGQ/AJENpPjK+zag5g\n6T3aiI6988V9hogw3JjTL+JSnYGJ6Vky6yqJu62bq5hiJxYMisMc/TlfnP8u6wdfogZjrFdKeVRq\nz7DLr2uPlxfLtZxhGklR2dBw/fltI/5l+S9Ptv9lFYkRtZTVGVO41I89t8UGqimAeslXFI1pKpXn\nd9RHbRXlmfACOpr0piRzEbmeGBsL5ZHipM+cCrp+7K8gwkWuZDVjWAUwkGhqGMRm8Pa5D/SO72Iy\nsW0aEU63LrPEXIe5b99Vp5jKVCZ041qz66fjyTB0xZIjf9KFCAYGZuqNLYoXL5R3UREmSrFJfvT6\nGaa2jqF9ajw8Oo87WSilxqxqe5x7ha608qnXQW7bD6fvvFxtxfvJxAHcP23NkCnNvSyjtR050U/M\nzff9bvOb4U+ggnNZLbUNpPyMUrAd74C6VkWYqS735J6j/z23nxcGQsUF/Q3BSNrA2+/rQ0DnT++i\n/b2XNRaRNm3AtXvHDY6aLaP3hCw9Qk0Az8pEMqtE/sSPBJyMy5nxUhxFecbakJBG7IwFB1p5te7V\n0xRh3sx3x6EoVm/8kBaJlCuNtRtdQqQNGQUG2DlXoypRasEKAJGFLqBQ42+Qj3FOHY9LhSJ4qVUs\nmckilKYJeQK8Mk+goqzsaom+rm9EnOgwg2yFLmegocfXoLXMreqwKUvE1EJJbroZD+6I0Nvdi+J5\nLo3YTEO2MGiUKQokUjWvthHewphZQmGPe/0Jp/uKENi6vbr2BppeOLFe7ty75EhCmT1lCVMwo5IQ\n+2zczPNZ/eFv7Hqon8Ee4P6EuUHvaXm+NDJRvp2EanvycKZqrlJrTIEANph0s2kGsZZUqWl4RqOs\nv+XZ8pdVJIPHlZFSYU3XlY8odtBPBn54UwdX9SCNt86G6x335TGZ614lyC6Xp8UQJR3sBUT0/iEL\n+rklNxvj3baMzcwEwIwqbWV2U2lQa34a8TIO9dDv1/FDRB5Vx8SGdmqnJ/2PTdMeSzqpe5GspNVc\np3uz5+jjmsLR5bqaC7uSLIIbG3gVONrrWa5d7ohY+dhDQ9n86wlcycLss1sc/mIKmS844UYm6XfN\nULpC12/H0dUxk/gse5Y0NtMKNN+iTcKbUsXe0b+Tcs+GWJMB2mpnjahm32Ho+VcBeOHO+6y81Q6T\nhhoc3RQYoiTQNpf4ai/eGnocb2k6yQ7h2qK6m4Rpr+PTtox9r4kNut+4DP25VcHI98bR0ATQ4mtV\nhC+PsaOQGYd76I1vSRJfpwzlu6juWKlzkKrEbzLAXWyIHrmFOHtU0c8tmUR8aWGWzskrPvTzTuUH\ntT4j8ehhSazreRR/U52y9kCnUOMJoEu47tjlDFexeUuFAWKCgjycKUtuTuXuRib1ShVGqhqS8m2Y\nUXqG4O4FLL8VgKWsFqfGnIc5FXiQxm+R/fEkFeuBNkhMxfU79Raw5EEHzfEb3ZwCv8bSAswdqCwz\nIr9TNxQVMsKHZrO3XL9NwKtHw6lViJClnamKVqpENj4SEPQahVDQZopSJq8V5zmX6ObA8g0Rvjuz\nQgdcSHI4SRXmlBTWYJiqZNc/2mBJGX1dRb7FxKCxd9BVnfJ3Ma3Al8cku9mzsaAbziYV7MgM1M4D\ngKFUhfn9TMytdWCVIOPH+JrnIZPqGwz/kfyXeyR/Wfivr9UcchXm2KiLSa8Xyc05ljv4qfwlvbFt\nrAt4VOqAv3WBlvhvnNExvpidTfAK0ZSnp2ckV9KEu67py9DxlA8PBsdRi1zrhWjk/cDrFMUksKVR\nmfynYkYl1RJTVOpn2wWWlDWDD4N+n5GJ7GYPLz7z/KHeEZxICefHsNOsLg4jNcGSrX0OMv3iGL1x\n4Q7JqM1kPEw11XpZrSyLSCrX97icyWkkT9TvbWFPAcFEcY4BeFmUkFFhQQOGyKX1hA7JJ+K4azOY\nsFWfgTxyH4jLdn2PDURluhopTuTiRSq30IQj1dg51WhzWiA6O+Yqnl1lvyToRz6Jfh8ncslDp3yb\n8ofZG1dR2GjpXrq1j1FdBqCQWmhDm57mpZjL6rTIKx+vQpJT9b0AH99ikhNtm81LU7GQ1VKhfHYx\n4tP9QxyGWrC8Zivz7/R+Ln+cPQXNuNEsbWuRF5dRiXkzSDY8fz0BRIz6lfDDL7P5+jnmdOtKFeb0\n4QIXeZq/6mnRhwMDuJuVk1llqe2xYkoVLW0ria3wRqqsQIUBVZ98h9mSj5v1MJnIbs4YjaJKYsSi\n4IsM93hMuyYMAk0lOLyAxzettAAYEJ6KRKKmUinnT4H/jv13z/73RXLgb/jv/7oc7rWJji1zOTNs\nOz25zJIuZ2nXGKYdjOiN0J0IvvXfz1zHvXiUCj6sVd1P8n7He0TcETHjRQM2IU8rYKC7KCqcLNmF\nN8mMX/ExU/0fcLPXt83ufSumAW/DTKbPuMes8VcYPi21WRGhlp6jo0ja7/Re1Ow6q7wER9OY97OY\nqN6t/byPj44jSU4N4+2uMsVGF4rr55bMcI4yd/Njfukhkr7eP/syea6AebZAFLtN+1BAK4ukvXmd\ntZAUx65OG+nqmIGxopCeXGZEr0g+ddqOPQU8LjDjTK9fCSIaU6pYHHqB936PpdM3pgTb5TBeLhKc\n10esZ/xnGfzm9yOuZGFlKPIiP8feIzhIbMbbztzkTac9TG4VQyd5PAV4YE0JIzjKBPaw+OU92MoV\nfJb3JgAv2x1nAnu0bVVHvZyMiWE9wUTS1/iKUCIGMCbgClJUbAg6wtJ9AnV1ZP8m7BRpzGch/tYF\n7PIWCCQpIkcy6hdrHr+4Gv8drfjWbw+WRiK881HpOkCABEaGJjES0Ykx60MVoW7FjJ7whBmNRaOj\nvBKIL3Gkh4uwvGukHXEzKyfMKYNBiLBkcqItMz5+iHkTLy3EPptVy0/QurFIrkFZz7rQPfR2TaFl\nByVffqWDxQ7lBK2tCtk1ZCuhDlm8ykamXBhLy4BsPI1yGdAnFStKcSeDD1ZGsumVY3zZ/Q49nNP4\nOVyE837pcQxTs3oM1vXn5QBdge57/AiIZlzlWGEhq2W67Ulk1PHBzFOsGf4jIz0TCD8s0E8m80uY\n+Y3wFH/KzkKCSlusGLRQKOx3Wl1gf//GPkC7N2nv9WY/AUDpK7/OGA7gXpPAqxfMcSGHs8O2UzV/\nPtt77WcCe7jfS4Tc6jDCixSGchxPUjE3ldBqbAOvGu7AMDkGS8robPqAmX3P40YmfRo9mTcs91AV\nUYJPSAU9uUw/zuEbWEqwfS6eBn/QNvlfkf9y+O9f1iO5MtKDyUf680ufM6y96MRxhtPTPJorlUF/\neL6ms10/znGHUCzN0MbInUwqKas2YDZrWMNsajBpdn4Xbjaxjv9YNGy9TWUW6zFr356fYjvxduAd\nLmR4ElXyzwu4ABxNKrXEfG/47GekXy1DT770T88Z6xaJQVaiHoRZIy0ti3lSrrN2Tx3dx64RVTxw\nGMCdxo6CNhRj4iXH1ELg98exnzOyETiZVJFU/mxL2cqoBkeLKhKL7Dg9ajsTT76AzEFNYGkc56s6\n05uLXKIPs75Jp/azi2xjOtPZwtZG1NjHwRGsfdBJrwOhRjSFgvfHrSXkd9ECuRN3qLH1IK7YiXY2\n+cSVOCKlQetNOptUkFut77FkfrIC9yWC/nzAhHQ+VVxkyoUxbOtziP7HpyGTNmBs2UBFqRHTzA5S\nX6VgJ2KuTwz5jaEnpzDA/QlnM3VdDAdxint01HoJ4c5pPM41Jh+Re9AU7oU6ZBFV4IASIz22aRND\nJUPsozhY1oVwqxQcc+/Qq7sZS/PCyUiy0GPvBXiRXexmEp+0XoeFdSvm3e73zC6YGmm6flZ2O8mH\n1/ti6aLiSJeddDv0Cq+ygY3MAuCH/if44NxQ5nW4wteRPdB4HLaONRTn6/8uTeloAG1Bqz0FyEyN\nUSpqtHNiaVurV3cDIhIwuEUSFml3OcBYHM1rSa+0xpYixphfwMWggGOK3sQpWyO3VONCeTNPGQQj\nxUHG0tIwnWy5K9VVhvwpHsn4Px73Z4tk398eyf+6rL7bjhJsOHhRkNotDj1Pt1YV+FgU81GQLmn7\nfdcz7Om/jwGcYVbXY2wI28fvX67nWLfVJOLLihY/o7L3Z6iHwNav6n6SbhYPeTJuNCPc4rEyqGSg\n+xNeku0jbLDIQYSNlIp4P9GM5iDfd9ExwUpRE0AcElT484C2IW25RyfaSh4QQJw2Cb+B1/Asj0KN\nhGmtY3hxrbB0R3GIt9rd0uY4dvTcxS89jnHrmkC95Febg4k1x5dfwfkLD6bcE+yse/rvY0//fSwP\nO4U7GbiZlfPS3AQcl7Zl+ApL9jGBHxyW8fMZUTC4ZM91wrnKvI8OE/HOGlqQjjfJnJ2qYGh/M+4U\nuNHbNYUePVPY+dEZ1r18izGPRWJ1fOcSrJV5vKLeQCeHLFqbi1zT+q776Goj8gPLZp7ny88PM7lV\nDK/EjUZt7oxRUS22pkqmGe/jyLK73B21BJtfYujew5bx9hGEexYw0y8Sc1ktKxjK+nDxnQ+u0tVz\ntCcGtRrO7dzLjo/fYaz3A5bsuY7vCwa0KRaFefNs1jKxZRy7+h9gUqtYFkgXMdtkK2uqklm++Hcm\nmgio7Okb3gxyT+Lxj2t5w+kqy47Z4qxIxLtnCRNGJbCi2ylmWu/k1+77mP1TJTt5iaWN6+kHj89w\nMy3nYYk9AzjDx+9d4PsuZynHkoGv5fNKiPDenHNvU4+hNq6fhTv505biWXAda2Mlc7+8TXaKOQs7\nXcSDNNZOOMH1XHc6OGXz6oYEwr81ZPc1Sz53vYQrWXy77AJuZDLV/RDvOu5nclgRnblF/ezOnEpv\nxUuOB7GiDHvjKm6t3cYwhMc6nKP0d3uCwkiEfzb2OkJkkTOLt92lzYdWPDIqY8p7CfTsY8+ckcLD\nqiuX8/XOmwzudxepRK1ln650cGAc+4mf8DNjEXO5eLcOnty/9T1aWxWxPOwU33v9ipMiiY4bHRn1\nSjK3Tu9gxgs32dJjn7YTo/UbnpiqKiigHomTKV3Ds3gv8AabXj9OKHfo3q+ID8aWY28DB/t8h5df\nOVuHbGV10C769/PGr7F3fThXcf5KAFimBT9hS9hBbQfMv+Wfy1/WI5nX0Y1t9wbyj0OVfDZawHvX\n9TzK61dGaMeZ9rNHcb6QVd1O4m1ZwszoMRTmmDBklYqTb0v5vstZPro1QO/ads7VFOWaMIPN3LPq\nxpMyd71KW5AQRCRDpSf5VvWp3rnvBV5ndVwXlCoDDCSqJgl3mM3PrOFNMLODKoHK0lBBzPSLZG7A\nNQIPzAHgxbcS2b1avBC2cgXta29T1dKPu09c8LjUjfTe1zk/fCsHu3dgVEQUA46LRP27P0RR8EEc\nHcPs+Tm+M2O+SuOHdzrw49B1vH/idQ4N2s3004Mpwxpnjypy0814gX3UYcQZg6G4NGSw5dxdJmV/\ni/sHR7md7447GXTmNp/NK6XT168Aor3x+LMTwMQK7+pIvX4iU1wO0jovhtODZxGQcI31T8bjYV6K\nSWUuKlsHEovtMDBU0av+InEmXVjX5xBjTgjySuWsRcg2zMdWrqBt7T1ijUIpqzPmNdaxHh3cU0oD\n1nN9KVmehLqJLfUmP/Ezc4if9AsBu/6h99u88300Kz8K4k1+YgOzqEPO1pvnmN61Py0tiwl1LeJN\nv6v0OPwyl0du5kqOJ2viQ3mr3W0+u92csW8gpznDIMIG5WibqoFgA1YpqshtZJAe1OoJ6aZWVMYo\nyEAHx435ZC1dlr5CdYMul2JJGSZUY0EFtHfArbCUyzleDOU4swZWMObMi1oKHy+LEpZ0Ps+R87Xs\n5CWmsJ3fmIq7WRmdHHIYvCmH3uvjabNnjt5zSw1UqBr07U8bo2ouzz3A5/ndOLLZG+tXPCjdlM7c\nwBssjwnjqz3FfPmitTaH91a7W6yO66LNK737WSTV39xiHcI7HDkzhSObvbFxqMHcSklGkgULWq5g\n/5N+hHKH6rfDeTR7MlFt7nJxxBb6HJ2BpWElSAwxd68nO8WcU0O3M/jEVN7kJw6YTmd/z60MOj8L\nvxZZ3Ev2YSK76RVuwZcRoXRsVc6ppFZ8vuEOxz5pQVSRMyH22dwv1NSK/QkeyaQ/Hvdni2TX3x7J\n/7q0W+5EBh7UfKVDTGV21k9wqkqVfNP5PG9fH8KIU5O1dBuel6J5Z2m0Vol87X9Ae05Rrgm9XFLZ\nwkzszYwY4q0PcTUzrCWaYGJV7XhalsV0Q6kyIMguV0+JAEKJgFaJAFoFtTmhg1aJANxerTu3Vi7j\nMr2ZGCQs3PTewjrvd2w6v6WM0CqRH7qeYcUHwexgCr+qQnlSbssP7wgAwYOBMwAwDrHCATFfPm0F\nVNr2S3+OMIqaBhkp+LB4RkdmLF/J7Xx3Xpn3AKMAS6588Slvf60r7spTmHNz5Wq+anewWVOqILt6\n5qu+5NoJV7Y8EfTv6ZXW5OFEQbGUD96/S0O9lAaXluTX27NKtUR7rmyDqHcprjUlgh4oVWIedk3Q\nr7qWGEooXp7MpFbxep//jJjDcdtEvsBQInIkIzmMaXqNdoyBgbhufFeRj3kv8Aa7H/nSozE/cGO8\nL+cyfahrMOAruX5MQ1MzUoJAJN047aLtUQLoQW4BTie1pC5VqqdEPg+5QuCSN/C00OcJs6OIBmML\nKrCgusqQNo2WdpVLAPElIiykdhRrJrXChqu5HtpQ25mlIpeXWWXFodQ2vNGvD2F7JvO0mJg1aP//\n5XtiLXUdn88pf0+ObBaV6qWbRI4tq1J8F4/WUXpAkKwqESK09RNIqRXfdGCT7DXt8cJcEfbqr7zO\nPJfL+FkV4ujSijjas5mXORLbjag2Io8SXSRCfvX1EuZPucb8OeK3G3xCFAL/zByWvXic+afaYKks\nZNCr2Rh3tCIfR2ZHDKMAR+4pGos8Z4USVSTAFNW2f9mt8d+Sv+xsuf1QSG/nJ6zPDtFCUNdvF9Xf\nfV1FkrDmXhk/xYXiaFyJBeXIEAv/wBEvfv3QW1sl/vXDQcxA4OC9LEow6iHlwegf8TAt4qzrAr37\nVtUb0cv2FscYwaIOZ7GiFBu5PgdTdFFTKnQ1b7e7xVuseub3kKDm/cDruHjqErSFMjcMPYTSqyqX\nMdziNB8eEC+qgUSFuUyEvfaEfKItpFt0U0frruGacmz8fkMOi0T9r0urKXMVIIOUK+bYOtVQujAe\nJ6cKjOQNGKLkSY4hrb5svP7XLbAsyoON0bzWW6ewo65lkXnAkgV39KGxbqblfBin23inSHciow5L\nynA1L0QqgW1bRVV1fIkDBvUK3C4u5NEYQWliSRl2clGnYStXIG1MT9meeKB3HwOVChejElZ1EgaA\nl0UJX3a8hDVi430kE0q3vnHzm5+uYNlPutxZdWOOYV2jl7MqKoQ3GnmhTFDQ98BDbuS4ME+2VNs6\n2N64iulsIa8x17F5/Blk0gaGtEjk4Fdees9n0aSgzsRASVG5zqj0JpnF98W8pVZY4+ql+93dnA0o\nrDGjCDsKUo15UOfI4UG7eC/wBpfqWxJgmkB9po611/2LBt5EcKdZjBJrzsBQhYm5EkvKCEPHpOvU\nQqyF6goDenMRqUTF6p9Fv5qTOzz59RP9KnBPc5GwBninSxgSVFgbiXXuYS7WXMFDY7wsxJy3NNXV\n+tw7KZTssdKuvHF1OMZlmRRHPaA9MbQwL4O7OXialfBN5/P8GC2q4BWYsWB7OPOX6yIKZoZ1okPi\nryOYc7UGK8rYsjiQmntl+CLg9AbUU5Ktb0CaUUnyE3s0rY3/FPkvh//+ZRXJ8XRf8mstiPhxK+0R\nRWCvviQw9BeyhZUcapnOrs+OMMP2BB25p+Wh+tz3MEu8t2JaIzbH7/x2s99QWG9mFVkU7i1kYewg\nlAFmDLk5Ue++xhZqXGxMMUTJ/MgB9JNexqS2eQWtrqmShFVxXQjq5aV3vKNhJIpFS1AjobjWhJkf\n6ii3h76RwY/uYpO0kNWSXuFMR4QFJzeop1IpZ933O1kvn6EFCbiRhWkvoUC8G19u5UzR+jRpbG8A\nuoeWsqir4B07NGg3HWVZTFonJ8ivJT7SLHytS9kcf4X6L7PoNjiHoCGV5JW7oJ4RyNkO/vRAFHaO\nOeTKbpswFo/cgjM5WmU24pN09vYXSut1/7u02TGUoQPS8Jcl80DWF0M7U2pHtmO6zx36jyhCqq6n\npkN7TuS2Y4pvNHP4iaJGgklfq2IMasUcjj+gD1VVq+HdmakcyhbKIbXCht33nNnsJ5S1ctZX9BmT\niazRIzFLrObMnL1M8Y3mx7DTmFuKDeZ1BGrrH4HRbHMU1fC+JNLWpoCpbeIZusddi9oqrDFjKzMI\n6yI81C2eg1GqDDiZ4YuFQh+xN6adDi0UMrAQB+MqLCyElZ6CD92JwM85gwDzLDb4H+aDQOEZdHbM\nxoZiXnS/Q5BdHis67uZYl0DO1Zux+KMIqgYGiF7swBivh0gWZmm9sLkHhUJpqJdSXSmjHCtuNgGE\n2GcIlJO9sYIkt7Go1FK2dtyMAfUE2OSz1PFncGjJp2vuMbhFIo8m/sT2BuHRfv3ddToYRNHTRXgq\nUT7CuyqpM6Hd2FL8OxbzRqGujuPNQFG4OLvlFYZwApfJNkRUtieWQL5y2sC3K6O5/vM21pZ2ZtwC\n8VxWlDLW5yHqNzviTgbfdD5HVb0Rq73XkLZ1AyZz47E2h6tLf6WDfQ65nqKSvwFD2toWY21fgw9P\nWOKxCU8bBZ0csulgrV+Y+7c8X/6yOZLfB7ZhzeNQfCuvkldowUGeD/TW0KhrRPHWV9xNc6fnEVEH\nYkw1NZhgMcEV82MJ2ClSGcgZlvG+tpbheWLvUt2MofZ/Kt90Psdnt/vzechlXvG9i/ee97F3qaa6\nwECPhnwuy1jOe3rnbr15jqODq5nbK5/uh1/R+x4jPBM4mqZD7bialpOtsGSUeyxXan0pKTDGwbiK\ntzfEkT8rlmtm3ZBKrYgtciLUNZsve1xmwC4RWjg7bBsbjxvx23tJmK74FKXKgFfZwDWDXjxsaK33\nTNPYyjYEud/P4cd5M0LwI7l4VRHSo4D4Q1aYVmTzgACWdj3D0rRw3Nr6s8n6M0J+f53XWauNs/fm\nIjcIoxaxAVvKakSFOMIKnfJxIgszTuO1813ONJzlVAdzlsWIgsYvWET6RxO07W6NDZTUNOYiMqcs\nw/03MZd7404xoZ1QIG+0vcPaB6JXS4B3AZKUXMrMPQhzzGBvcjtWdDvF3OsD8SOBR/jza/h+Xo5o\n2i8eLUpMSgN93VI5l9USuUE9KrUEpbUPFKfhQRrpeNJSmkKtyhA1Ei39jYZKvY9rCpVKI2KKnTBo\nqKU/5ziCfsGgRsyopApzNl69wKs9dLUeXjd7UNrzDKV1Ym3eG7eOjr+/3gS1JWFRpwvMvyuoTz6W\nLeOcsqcWXWhOBVKZjHKlMZ+HXGHx/Z6EcZ0bdNP++zx5zf8u6x920qIjzQzrsDCqJVdhQcacFbxW\nMobHB+Q8qXbW5hI1NVFvsYrVvK291teWPzCv/APt2oqP20pAu+k4GFdRWSPBPbCOxBjrZo21vKTp\nuDrA9TwP/pQcyYx/9+x/XyRb/s6R/K9LyecOPCqwR25jRhZueFmUsOW7k3pj5EGW2H3uyws+D/ki\n5DL93UQl8+ITQfQ8MlNrbYZ+asDkVjFU7M2mpt6QMqzo/IsNHuEN9EO/eZOmglgjHXMuYzFWJFa7\nOOosIAP0q2rXhB+j2xBdU6UhnMCkIhcDQxWpfZwJ7yFoRSpKZTi3UWjHGVHLct7TVpkD2FFI+c0W\ndPzQQKtEAGowYUHHS3pKBEA+RWxU30y6xrafowjlNi+3iSRviYSOF71o/ZIhVZUNuKrSqSpX8ySu\ngTm9RU3FgOPT2MOLtF02QRTnWThQ7B2OnRW82euu3n00SgRgcUQHLpUcZHT/RHJSzTi+3YsGMwMc\nXU0xphq/kRUYltXzVZ+9RHY2YdCkNN5Zo5vbS/RB1vjnoBZ5WiXSZ0wmBlLIs/Rgwi4RykzqVcey\nmDCGcYwRngm8uc2ard+30daR1DTIGOv9kOXdTjG9Whd6S39VvKPn8g9zJceTbb4/4EEant2r6OGU\nxowFCZjKhPfy7vXBqJHiGiC83QapTtFfWfIb0Eif49mJTz69LChhgNoGQ1qb5UBxGrYfttRSlRgE\nDSSTFpha6YyQ0WYXCQnI4/NX76DwMsZ5kBwFZhxhFKuWiXoTS1sdY8Erbe5ThTnt+qm0SuTTX8Rv\nktr1Khvn62h3Ov4uwnj19RBAHDJqMfCXYmxaz+plBwjxqdUqka4DcqnEgpChIp93iDYM5Th2HqIA\nM63xO8xeHIvTasEq4bRKlzM0lwnvZGAjc8BL9ufZHvgLACt+qufkDk/mtL9Ld+d0XmyrIZQDAAAg\nAElEQVQlal3kMggiivpFfejsIN6jTg5Z/GNsA6NfTcYhbiR97B6w4PYkRns9pF/nfAKIp/SxjKEe\nj0mItGFOwC0+bERs1shtSMj7n3dn/P+bSCQSqUQiuS+RSI485/gqiUSSKJFIoiQSSfAfXu+v6pGY\nW32KoswArOWoSuufO1bTdrapyOQNKGt1m9aA8Rmc3ddCr7kOwLTW0ewo7ERD8fNjrc9q6PS0GJvW\na2klnnkNs3qMjBsoK2pe8SxB3aQPvE4sbWtZE3acKcf/uOR22KRkzu9yYTCnOISumt3cso693fcy\n9OQUDCUN1KsNMJSpMFDWUYsx5lZ1KMtUmBiJZ9DUdGg8n2bfk2psNnYl51XRWbJpjYpELsVDVkRO\npSl1yEWzJ+SYTX6fR5budPTZQP5HulyIpjmUiVl9Yy2AkC9CLvPV/Z48XUXdVKztayktlOs1ppod\ncJs18Z2xtaqmuEz/2efwE2t5nXpkGFGLqa2a0mJjvO/3Ijv0PLUNhtqKdM0aMbNQUlUha9YIbUuf\ng8x4ijFAH0HUKDYtkJakNmNNkNKAVAYdrHOJLHOmvsm1m34fADMLJQ0V9Xq/hbNnFQVpcr11rHdb\nh2pKiq2goY65X99j+byOSMwMsK2v0IYVNSKjDiVGmBrWYWqopKxGpv27aRX58+TBhg20nTULGXVk\nT1uBw7aPAHhhZhL7N+uTPEolKlRqqV4dC+jWmiYysOnqeeb27a41LOxNFRQqdM9tbVRNaZ2JXg3R\nf6NHIpFI5gIdAUu1Wj3yqWNDgDlqtXqYRCLpAqxUq9X/tPDtL+uRfNflGCoM2Hj8NJ24wxvd7mnz\nCBoZ5vGY19reI5hIFk/eweAWIkF32HcxCRNXay0mbggLqgFDgomkA/fpwwUKCpTPVCIdehQQJr0F\nwNmey/TqSDR1ItImHkmNwpAV3U/pXWN22zukjRJopDYmBby9TbdemnKAGSCU5Fvtbmk/a9+1CG97\nJ4o8dAV23/U5R9igXKb4RmNLETbyaro3ekAvu1XQiiQWvZDLz2Fb+MF/J/8Pe+8dHlW5tf9/ZiaZ\n9N57JYEEUiBAIAkEQpfeO4ggTZooTUEpIlhABBGVJlKkV+k99NBCgJAQEtIL6b3P748nmckQ9Ph6\nzvle7+/VdV1KZvZ+dnlm72e1e91ri89P2BUmkLXEmooFn2GhU4qvXjyL371OqxmCrqO7aRwVaFPT\n15WCSm28eIIR+fjzgJbcY0bz27gY5GFsLqzkge7P8Vt6AIC1w3Yx3PkhHnUMswG2ZZRXQGcuEqJ5\nG3uvcvQ0KpljOJQrl2vImveUD/hSeT8l1XKM5OWUlWgwaIqqlfHDHGukMmhnlcy6dqr2s+48pw23\nWRZwiZyBAglWj5xbxGdE5lgzaEocYTqP0JWKhPW2zwXAImViL0Z1fYY/97Eljak13+HqVcCpqNEY\n1Ih8U1GVFh24gptRPmOaRLKoqcgXVVXK6DFShezb/8KbbsNVbXSd9PPp+q4qh2KGmI8Bulsxt6tQ\n5jwAVhivxUMnDTutIkqdtRnbRdTFfNl0D6vansOpNh4dVN7qF7Mv05oIHD2KeGvMSwAyEvUY0E08\n1w352aYuF3lEiUQCNZXItWuQbM7CwLgSq5IUst4Rc18POkj6ZSOBvcW1unfRJ7tcj94WwoOvVyJj\nLS8y3VvUj6TvUYFJtPxFTuvMVgdacg9b0hi2oxUtTDN5/MNmOjq/ZPSESCzIUo7R06hicLcYerQs\nU84RwPzOd1g07C6f7srHzTAXj2cpaFcVMNxN3M87vrfQ7yWoVfo6PSO/UgdDCmiqm4q95X8wY/2/\nKNkukUjsgV5QxxzbWPoBOwAUCsVtwEgikVj9zr7imH9Xj+RkTzd6nRqttJoAVu+7wfyhvx+7rZdB\n0sMs7P+KgDok1Gi3B+x84U/PkYmc3u2IAgnfGi9lZv4nf3iceut0yrLHbFrSGA7cUHInrMZ06/w3\nbguW3uBarbjuxJFrcdo9R217P9kJjtb0bjTu4233WPF2qz88L8Aojb3sqlYHDSDThJoqNp67TGmR\nJh8MFGGi9lbJLA++RNjBsfzWcxcaOgq6HxqtNjRt4FKcDi1k45VrKobgeqlrBQuCp0temEGiiw8l\nCSLMtDH4N6bV5U4APMv7cWxcFzz3zhDxcen7SpbgesmbtpoNEa1ZHCHOJZdW817zCGVO5HXJHbcK\n058XvHFbiOwG4TWNn5FJnhF84HcLz70zWKG5lJvDx3HyFyelN/gWJ/gN1W/gpRPD0zJPtoceYfzl\n/gCNuLwaSmfbeC6mueLESxJxxkX2koQaZxxOtCW59221fVfvv8HC4YF0d3jB5VfOlJVoKi32PysG\nmhU4V8UQhU+jbV05yzWC1Tzphu1/AcreWYH+lgXUoIFES4q8olSZr3qTXC89SJDuoDdue8/7Nhue\nCFRhxpivsH4Dr9oUvmcTovan69AkVlWfYpG8J5fvNSWo9QsuHbMnpFMS4Zcc6WUazW9J6vk5G9LU\n2jT7tXuFSWIxl9Jc+I94JBP/6ui/LpLNb/ZIJBLJfuAzwAiY+waP5DjwuUKhuFH3+TwwT6FQ3H/9\nWPXyt/VIllxuSxOjHN5eWYs/Yn6MXqpTYFiQxaj3Y8BenTbF4z1bzob2YIS7sGp2vvBnkX84p3Y7\n8UXgOexI4Xh+O0b1eoKBpjo9db0Me+85NWgwbUUUF5Y0dvOldZ6J5ReiWNJ063zahGUqcx1hnOfk\nTMGvtXBaEl0RnQudds9R8z70NCo5WtObxS1FRXo9cmqR/1VSTqu8pb1+KotQv7cwPlbvF2igU18K\nPqR+zs9YtPIaEzwfcGrFLt5peh+niFfELNKmtWc6puSQqGvC/IPNmD8vghOJHkRUi/zKgInCujXn\nFTHLm9Pd9TZ3D4s6A5sGPTuG/VpEO8R52+vfpGmIBmEDUzAaY4+eYSXTrr3FvC/v4MUTDDXL6XQ2\nnF1xYrEL9qqA2mpl+2FDXTH3p7V1lEoEoKpWyvUMByUybtYXkbjygmuBS+luH8enXqJZlIrKH76b\ndIDCtz/H175YCQsNRSDYzD/15FSMNZ57Z9CMp3ymtYhXZzQwkpcrreZ6JWKN8PKelok81JpHgfzi\nIzjTMrHmE+df+TLwLA3FkAIi08RcyQ3FMzqxpfAarHpvUNvXST+fnSv98HV5RWfrBMpKNPHjAbOa\n38ateYHavr+GCe/P3yyd+X7X1LYN+fAFAZ6qmpH6FsjautUk40AZunw0+aaSdXept6qLqG6oGTpb\nPubDCcLD/2R1NCsCr6o8+HoxEegtv+BXTJb+pPx69PuC821UqPCoNjxpi8k0Z9pZJbPxaQBv93rI\n9MXinX3nIxHO3M54xno8xC0ujOQ4A1odmkzmOU1WmB3B0aWQqJ7reXZcg+4DE7mTZIytrvDk7PUK\nWDD3Dq8cRE5qdtdI0DHi4U0LLuX/ayPrT8v/Aw/kciZ8+kD135tEIpG8BWQqFIqHiPjufyQZ/7f1\nSCTSJShqJYKeu7buhZHIQFHzx4MBoyHWFOxXhY8W/xTB8pldoKwADTttqlPLeTFiHR6/zmhUWPhG\n8QyDmAuvfVnPhtqYFbVeZn4WyeLYM8w07q/sWtdYfn88mhJs7YpIe6mPS1QoCS0uAyKsVosUDXkN\n1ZUypFIFtbUS5NJqzOS5pJdbNjqUlFpBeC+VoKiVcKrXTnqeHN1oP6W0GoqnxmZibosF0pNnxKCO\nknJ52JGCr2PI/SUDkKAhqaJaIXz2+grrwZOec+AnUcWfOfZLrHZ8qDZ3bbhDpHYrKspVvr4qV/AH\ncwNczjtMqIl6vkJDo5bq6j9vf8lktdS8VgkeOfh7fA9Mo2EXzHoZzH4OIBL6r1vJf04UtO+ewc2z\n1uj1tKL4ZBYSuQRFpTiXy90QEgLEAo2mBKrUr0HTWZeql6W4PutMvPclqHn9Gv94zgA6c4GLhCHT\nqKWmWlqXP5M2GifTqOVi9hE6GfdrlOt5/fq0ZVWsanuB2Td6gExC6oivsNs5l9jh6/H4dYY4nqSW\nWrkGiorG9O8SLSkrtl3n07fbKPObQ9jXiD+unvPr+/OXmdollOhen9HsZPW/75FM+auj/7pINjX2\nSCQSyUpgNFAN6AAGwCGFQjG2wT6bgEsKhWJv3ednQEeFQpHJ78jf1iOZ6HkfE3JZ5/aj8rsOiot/\nMEIl9vvPq31ePqk1ptMFIqU6VcTPf4xuhZUivdFYgDZdMpQWHoB7zCZxfrW2q5LX/m0sVkeysQg/\nQvMbyb+7T8PxtqSiZ1iFr2kG7bnOlaU7SXspCPjqlYipVim1dY9Fl0EC/eLcVFhvnrVP6eEk4vW+\niMZQU7zu4scDapHiYpiPk56oth5xUoSfuo8Q8f/xHg9w0FNZxHMKJ5N6W3VtMTSlLbdY7LxfCbW1\n8luFw0lxHq3m+ugrVJ6Lp584z4GfmrDATyyMg3YE0scpRnnP2rJq7tBWTYm4EUe1REpHm5eNWii/\nLqEmA9ANVRH7LWl1maktD6Il+31wBgjW6AALUQvyuhIB8D0wlWFu6g2sBrpEI7OUc4AhSq+lXokE\nEPG756ovoqwXB/1CbpyxwcKujDUePwOgqFQovb6EgHCwbUFbboGFqBPyMVUZRVr5Yl57DFrFQEf1\nyn8hb34el7RUPc8XCaM916mpU7jVChnLW19S9g6pz720NUuho/FAapEpvTs1aaDk5vrcFEoEoEaB\n3c659HeOZnN0S+U+ForMRkrEtK5AdWaTG3w0sh1TmggvqTV33khCWr/uTu0Sigm5NDv50Rvv938s\n/0tyJAqFYpFCoXBUKBSuwHDgYkMlUifHgLEAEokkEMj/IyUCf2NFEp1nTh6mPHoOI9kFwMDj6tNR\nv9DUF8nVi/1wA+g4XW2/3K/U3fbVD4Np++6bwloK7py35iodlZ8LV4kQpc9MVeK0YVjl9+TjiM4Q\nf4OPIsKQSsW1Xsg+8sZ9pVIFadhRUqhJZK41Nwii40cNWX/FC5RbocsQV7GAnN4jYJq+pWJRvPrd\nOTaMFWGXSPywP9GWUz/N4SH++LbPxiygio5FR7nUZzv5dRQgZ+qOEfBtId1KxDw63wlh7fMwSmX6\natd4m0C83VW/wbah97DpLuaw4nERxnWRRwf9ArhT9+z79GbVQ9GI6oYkSA26XKlfj0ZSLX6FK/sg\nkym4ku6s1moXCSxhqXKupi6LQlNeQ+llAWG1OvAOy+6Fsv7OYDX2XIDzGUcwmSLuc1PICR7hw91X\ntoCC8Z7qnRjrvZC9L1Q5MSm1HEpoxp2Q9Xx58LqSZ6te7tJa7bOEWvK/+oqWHV+Rj4kSmCGhluRi\nI9r3SKfIxpZ3v+mhHKPfpN7TVkBaFLcJRJIulNmjPFUetThfhFk3PmnDoQT1FtMg2H/rZV3Qqbrz\nKlgSclU5dwA3CEIiEX+HSMJZHNGZi2mCQqXJJLG438xyUB4rXE8VejR7v442x6s7ueNX8+E39zlw\ndoVy+8B3xbt25GUzvogMUn7fzSMLQmfQ0NNLmvctK/fcZN3TQEHQOUworAjaNLgp4dGu+03cg26Y\nOaBQ0tj8HUQikUyWSCTvAigUipNAgkQiiQN+AN7cyKWB/G0VSaK7I64GuQRddyYKgWW/M0egRQxH\nCPrziR8J62zOlNVqY1PPaGPSQoX4UVg3U/6tYa9NqL+I256658/roqX3+pRLyFogqtLvnFe90DWv\nedLmSxqHrsLshIXn0y6b2rq2oGHm/WneRsXHpa0rrGfLOQ6Nxqsb5KoPFbbqOZvyVsLqe2Boz74Q\nARfuPzGejrN/omBrIiPO1FCUZ4hWdhXa3pY8jEFJfVEv1wjmPuI4+T8lYkoOtTWNrdtJXt8r/17v\nr2qlquVjSKWZ8FTG+UUyR/oNAD2nH1Xu83DH9sb3+Nq9lVx8haRWxOV/Zxc+8rvKqSX6VFepwi3e\n8fWeqwSJlvpveELaG5u7Iij9dbgHFXXtbD8ODicj+3WvR9yzVqCKOn7gVGGh/xTdirvfBKnt7W6Y\ng4adepJ6vGckvX4eTs49MR/1HmQLotCw16adJAXL/CzluYa7RZGboYXhMFtMLVXGjcLau+4PCSYz\nXHhdPP3yGn1XbSCUqERHRqG3MATMvunCi/YCJDC+7ll+56OndPxMKLjob5a/aQroZPMS84/Fcz15\nXqRys84a4d3MnbSKjO5mREp9iQksUW6PvicWeOF9CtE3quRBYAuG+8ygoeHQaXlnvpO+x7uLnxCd\nZ8EXD2bQ1P61m8oSaMzTu+vaCV+IxUG/kH8Vwvv/uygUiiv1iXaFQvGDQqH4scG29xQKhbtCofD9\noyR7vfxtFUkOZrga5hMenKSkSLn6jcCfF+4R4ZurnwlvLnWwOixYkfeK/A3i5Z8p+ZbtTVcBCvqM\nSyCu42ouP2hG8qg1NL93QUn/bVz3AleUKGjLLeZRp5waPKv9i1SNhKQooMF/U5eNZsKip0jqLD4Z\n1YTZC0Xy6KY5peOXgkTBfMlqvNuoKFcMaivYGPIbdzPVK9vjR6yj5l0VmeGhmFPsChOU3qPSdgOw\nar/gWtKRunNv0A/8OEbB/mCRMxg48QVtv81n8NYlBHGd+Gg5qY8quWPaGh8PCWatRBI2zC6ezeGX\nGL9+D9OsBIfVmZzF5FoGMjBBWIIitCLu66OgZUS9vR9vHjMj8gzv3NmOppsuFTnOpL3UZ2vHo6y4\n1oH+v/xG8pg1TPlGZan+PFYsfPXhjKoRgsSxcoZqn8VFv6KQwvGFByh/R32B+6Su/EAj8jIvcVHq\nloWSz3msaMHV/EP8+tUmDGrF8S+8OoIEBeusZISUiufBUxKLuW4F/SbE80ukDzu+uqp2jvrf+9p1\nVcOzwVOEhb3paQCK8L3YStKU1nycVltaVsXhisrjfWBhzzKnCyQWG9PBJpFzb+0A4BG+BFQ+5+gp\nYyzzXxHUKx0k8OuLFpxOO07h3jRsq1ThxZVrtvJk6HcMd4vCZLoLP3c6jJ2LyuP40Ci87pJVyrAA\nkdNSlNVg8KQEY3kZ2bMv4H5BeK0TFkUr/+16+DKgwOI9rQaUPyrpbJ9A9opYOnMB6xUqT7q+h739\n/ky8Rkzk7EwZF258CIgGW8GlCXTIbUdvx1jlfBYXyPG/+YhlWWdUJ7BtTpGJCzNYz/LoAzwrMGey\n9Guaajzj7sAflfdV38b61C6hSPIwxdS3Ct1OjfuV/GX5P97Y6m+rSNq6PCOhyBjfSRDtKmCgPUd+\niLm1ikAxhqa04Tbhn4s+Gs2MX2GmVcrqXsf5csouLq7cTd6UTmw1aI3USJPE4zq0vTKJZq3y+P5p\nAGnYUFKtiQ1p9BqZSLOAXLR0qols3YN10rm4EM+kxU+UdSTHEz14e77wZiQN/g8SUhYO4dfrIVRM\nEIvicd9VtAzJooNmOCd77mKa2WBQSFgnfZ+sBGu0dIQnUizTYl24G2t2ipemk4Go3B12ey7L2/Xk\nkw7C+rvk+ZxRFwbRirt8pDcLALOIfMIsbqDb9ChTDvqjAFp13YgPkSzaNISZvTowfb2UZgsvYa9X\nQAfDKEpfVrE7rgV6l6NZMvEwF1JdmRjSie3PfDlaHIqfRyLTD/mhGDCa1gPXYTDYhke51piRQ9SQ\njby460GLbUMIdXvF7CM+7LYfgU5eHtapZwjhKtEJCuZ6X2VB+jg2xLXlE1sBsW5pnsb4baLt7RQv\nofi7beuAHSlcvKXS1meT3aitVBCe4oBUquoGeeLDfch++oQ2YZlIWnWgVccsFvldBTNnij/tidOZ\nSzidyQQrByrqivpOhFnRtXkZ4xdE0zEohfELojmh6M2dgZsJkj4h7p31WL49i/ntrzPUtC4HYGBF\nK+7SWibi802NX3FhmKrl7qnBs1k7fR9vL4xGnyLGBJyn7yfm5GNM77EvCfZLJueBnC4nxuGonw/p\nLzkc44zRGGFmd2iRTOjiStJKDfit525QwNHueyj+VXgvuYOEF2JsXoFEosB733S8QlIp8D3Bh5fa\nk5qgjwcxLG99kY1PAhg24zluxDF8pui3M9P1Bt3t45jd4ibnkl2Z0FSE7iK+FmGwYP1BTFj0FIcz\nmVxOd0YihSDHOSxvfVl5j083GSCRKIgyFEzEFwkjXBLS6B19Xlde0ywgl1HrZjN7zF3u0Ibr+i4k\nrUlhTXgT1k3fLu5HXkZ6DuytHs+ct+5gplXK+35b8NV9iPuDBL5O78rOToc452qHf1AZHx5yp69R\nOJM6R1NhJceXh3QbnsQ4j4e4GOTRulMmnSMO4zD6ze2X/xF1+duituRmP6DIS2ZjeDiTgkLVtkup\nQYJCYODfUBk+xPUJ++03wFURhtnc8RgTr4g8h6VdKblpWsyRfEOuRye2PGupNlZLWq1ciOpF8AUJ\nJJ5cq4bKChm/h9pawOesQvQx6cRFLkm7MmJGNEe3ulBapImWrJr+k19waIs70loF1NDofPVVvg6b\nm5M8UTTRihqySdnTepDLUw42iI93XNqOK5/cZF+XfbxTNIGi28Vqx5NSi3dgLmZJRVTVyhjxcwLv\nde+ots9w9rCX4SiQEN5vK/Mre3LBdgs6Wz5W7vN65fVHrCDOrT+HFG2oii8FHSMoExb1OI+H/Bzr\nB817wePfAAnzpV+yuvZD5Xh9o0qKC+TK37QeGSTXhFle11nzuB1IUCaF6+c6vOggIQaD1LsJSqTI\n5VX4VdzlDiqmZICkUWvpv6sD92lFX8kJjil6v1YZ3VjqfwMpNbzDFn7i3QZbFUhRUIuU7vZxJNuY\n8jRC1UlyDDv4hbGEWCeSmIGSNqUhr5uMahRIlWGverEgi3ypGdsjLlD7QTFjLqmYDRqO15JWM8z9\nMTtiBTuGXKuGykpNUNQqj1+DhrISHGjUQ6f+83y/a6x+GEK919mBK1ylo9r5PHJ7EGuqXnQLkDbm\na/bENWfuTVWYc33QSRZeD6EY1SKvZJWQQM+RiUrvwsMomyWtrjL6orjP1yvf/5z8B+pI5v7V0X9d\nJF//w7X1X5fKnDScDfKZFBSK3EPVeKrXaEE7say7cOvNrMsZ00QVv7XULmZ/vDemdV6EUZvWSiUC\nUDPOl2qFjLxFPdmSoaK0Nv+kLsfRmMUEs9XNqVcWlXXQxDAuENhNwF7rrWY34ljFQkb1uMHsFjfx\n2dISi2VN2LPOQ1kMVlGjwd6NnlRVyKgwa95IiegbVRLYXYTskieKUJq/eYZSiQAcrBTFhy1MM3m/\ndRRpa0SXvB12rdFJyVI73qwvIuk7M5+oW+a80DXneoajUom4NMiTePW1Zbp3BBM87xNydAI3Ttmw\ntkr0c5nT4ibNTTLVlAjAZ3zMQ0M7oUQAygpw8xaK5OdYP3DvAI9PAhJ0Ak3Y8rGoRfi01WUcSKK4\nQE5I7zSGz4ylp+MLVgeJ38xsuSeVo/Qx/cy7gRIBkNDNPo4Qg0F0to3ncskRAkKz0NCsBUUtMwpl\nWDoZE8oltRyL46453KcVuvpVZFqIhfePlIi5dolYQF3b05zHHLIa0+AHsgBtQ5yaFWFlX8qZFHda\ntFXlvAZMeoG+l8jJpZYYUONqhoN7EUNW6KiRg9ag0UiJALzCksljIxnVqhuHenZS27ZhyBH0jQRL\ng9ywVqlEBrk8ZeyHz+g6WYQr21kl884nzwCUSmRZwEVqFFJmr3xIcK86xJpCyvs+N1n9MJgunEWv\ni+iJUt6lKavanlNeb0CnTGJNT/PRxJtYLBcQ8CnLxLPpcmAWc292R1dDxQ4843ovpRIZNPmF8n4X\nTr8NCkh4qurpEltgzjvZ45WfDVqoQA7jPR5iMlOVG5J3CcHaUeRiptVV6DdkRfhHfl/+th7J+lOd\nmNFTvR+GhqQGt5ZFxNwzVvteR1al1olud9hBRt0aykjbB+x6rl75ezDpHIMcxQI53vMB22NEwr1F\nVkeiLK802FMBUg1lDYtcu4bKcpn69gaeyHxWodmyvbIXxQd8iVlQSxZeF9336rmcAAbPiOfEehvK\n0UGqL6O2uAZd/SpKizWR9J4F59ejKK9Vs5r1NCqpVUi43e8HWh4SvFH10rlfMhePOnCk+6/YmhbT\nZs9EFrKSz1nEuZs/U1mooE+vseiFmNEiOrKOMRW+PXmVmb1EeMm2syZRt8woL9XgUp/tRL7rxud9\nmqhVct/sv5nVR8xUfF7B79LFZjHn9zuApgQnrTyCbFPZHSvCM68zJ8/X/5rVxXMxNKmgME+Li0n7\n6ew4BO+UjjyxF3Ov7PW+5Alblzers6AVLGl7lWW3hQLMm7EGs+3zyBj0BZbb38dAs4KFvldZF9+e\n2H7fYrRNvbPlxaTDPBymy/s3u/NN+9NKmKq+vJLiSjkSFIxqGsXOZz5oUEU1mmzteJQJV1SMvFJq\n0NGooaRajr95Og+yVcgte1kqKTV2aufsYJ3A1QyxCHa0ecmVdGd0NSopV2ggQcCOfUrCeKR3AS2d\naq5228zyB505UVfRraNXzcOLO/BsK5pxSaQKUVdVJ1FDNjJyf3CjynZdSQmlCj3+E7Kw9TU+jwgG\nGtYACWnEWC2TQ02l2vh17U+x4FEXyopVz+rvcctFjt6E784pXO+3haCj7+B0NYiADnM4iGBgvtD7\nZ8JOjGs0jjaj4I7Hv++RvJmU4r8qktX/eCT/dXldicxpcZNqhYz8LDkDJgorxxJhucvHqrr4mVqV\nM/LCIN6eHdVIibjygqgBmrQIFFw/9UrEL+gVj12u4R+ismLl2rWqQkjgXbfXawXUf//VLOB+trXy\n+6/4UCgRp9bodjIXSsS6KZryGg6sd1US8fkV36HLkGRK6142RWwkivJaTLTKqEWGkZkAAZRUy3HQ\nL+Cbpp2VSqTv2yKZn1wt5mpPzzDa7BFcD8d0xjBo8gvuxXRjZPf+WDuW4lMQxY1MRyX/08xeYlwq\n9kRctMKvVNxjp+PjuTIWilCPP797pI0aKeSEDrPJu1QXjnLTI7HYmN2x3nzwTVoG3DgAACAASURB\nVF2Pj9fo9zs2q8WKDArzhELt7CgK++qVSAAR1PbxQCarJd7UC5UNJeFMghtr24vQiqfLFmqLqjnf\nQqD4Fre6QvjoDijmB2C0bSFhqNcRdXYcwEl7EQrUblBjIqljEJm4PIEDBh0wMqtQzu2EF0vUjmHB\nKyX1f762umc2xCtJ7fPwmbFcLRRV1ybvuWA5QJyztFpObY0UDwPhwcjOCQBARZkGbY9OIeJ9VRir\nrESDuRtVHomiVgJGtsrGYGP2tyMKHyZ/qgKAAJTrqaz9gS4qkswZq4TXPtWrcc1Li3bZjb4DlEoE\nwOoX1UqrG2rWqO1BvRJZ3voisweLc/zm4K1UIvWsxq8rEW1EznOtvTAS6tmuOxzbwkEGYzpXoOfC\nToxjcjMVqKY+J7TaZsIbr/0fUZe/rSJ5XdZGiYS7kWkFg+LFS5FV182uYJuq4E/fsIofQo6z9TMv\nFm68hzZlGAwVhWPxuJF+7xlRt8zVju2fnYJ263EkeKooF9S9D9jw5PfINRWMmyfCCCeTPEAiXpQ5\nrBG0J2mPeavZLaT6Miymo8YkC5Ck3VRY9HUS6SPCVpoWYhXV1ReLkPOdEGILzNm6UiyIHkbZyvDN\n8xRBEbN3toXyOE/KHDj4gxsBb92mNtSZtAR9pOk1BFomU4Qhw/iVY933ANDGQqDgPumlQh4N9s/C\nzVQ91xKFD7oGKtqWrSu9cK5rJyuJFf92G55Ey47iuh4NVkGF+4xP4LcInd/lqgJRj3H1uB01NVJ6\nmaTilt4DswXuSFBwO8ue1BsCvWdUB/82HWsFTTow71Y3Ts3WYstQQUx4gS6Njn3+sVhwpoSr+LSK\n6moyjv9kRXlEPgU5WnwfcoJ32AwpkWrjG163fmktK3beUhYmXv9yuNq+v37rAaUCmdd9w0r2b3Tn\nm+MiFPtq7Bd80kooziahojh2+S+3uNRnO5mzH9PqigceCNisX/BrC3xBmpLBN1GrKSPcozg74D1G\nNwjt1harjJ9DCV7KUNj6BeIZ2ffCm2HvPac+H5I25muibqq/D28UhQrVVXo5BzrNUn7uPzFeqSgW\nR3SGQKE8mrfNgQ6iZLwwt3HM+IeQ40oo9vZVKoh+L8dYznwlIMS5X4tncsPpK/wQLWjwO9q8ZFTs\nXQ5128v61D/my/tHhPxtFYn+x8Iy6e8s4IqWOsWE6UfwKk2HzIwKPJfa0cQ3H7MWIm6+pt0ZTMil\nMFGDFemhBMkjSDqvwwj3xxTtS6PnqEScSeDQZ9/wUZNjvJ2qg3ldf/O4AlO6OC+mnW68kh21rVT8\n6899jOuK2fpZiu8mf/qYac0j8GqdSyvuEXFRUJL0MY9AKq1h09pzrOV9kloE0X+1A52cXzJ72T20\nF59lgucDpoSVMtnnHuO7PKJqWFM62CSCTJPuHZ7yy4h3MecVWSm62GzzozBXLHZ2QWsIDnhO9+FJ\nXL58lowePlSsr2So6xOau+4DIMQ5kvELokU3ujprdNPi5njefYi1ThG1QUHoG2byTruH7GU4fc+M\nwE6vkKLiGoIdHjLnZCuwbELngSlMuxhG5Sx/bJxL8OIJXQwiGOr6GJ/AHIa5CStYj2IsdEpw+9yZ\nIOtkdq7aRrGxGSeHikX3y7o2q1o61bw4qkfy16LRWFtZBC1MM5VzDTBr1F0GToyjt1kEtVOXYh/3\nlOc2Z5gacJkA7hJgkcolOuFuVIKR7Uo69CjmYxsbmo94SEvuEWiZzJGettiTzATP+7QdVEP1jGVY\nkMV4j4f4m+9milcEPaaDD5GM7yz6sI/v9Ainkjgli/Fv5dYckAvqmG7DkuhqGAGaOhiTxxDXJ3wf\ncoJEPQuuLzRjzvybLAqM5OWAJwRPd2DqB3fp7ZWDJ8/o6xTDFK8IJCP8sdMr5OM+fljal/K80Izh\nFwZjYllOee8IZOZyri8yo9Px8RhPceJpx4f0/FgYIwMmCo/ThXglb5ycCnrNdKKqVkpM8+YED15H\n+HMjwrMOMm95OkaGwvAY7/GAIOsk3Aue4EASkzwjGNYunC7vJFOxL58Bk4Q31HdXR2yNhJLQbmVE\nABFsarWH+RtEv/sjzZbx9sYUBq9vQovAbCRaUqZty8XcU0DRJ/vcI17bg8oCKVO8ItCgivKtVfgQ\nyb0vTRidPpU+Vg+QU8EQW/F7Lx1whhHuUaxID6XrcMHOMCngPl8cuI4XT7iRZEEWVko2b0f9fN7r\n0ZHVbc/RaUAKV9Kd+Vq7AwPPDqNt9ze26/ify/9x+O/fNkcCwtI4130LXc+8o7bdlRfE46b2nRnZ\n5PDHllU3znCW7n+4z5+VxFFrcbq5H+JvNNomUDAiLOCW1A9jx8XKpkJq4tkZYv4c7cufkfq4fhe7\neM6nujba7kASyTj+qWPZ/OxPzbjTSq+vXkJ6pxF+ojG/1GCXpxx4Q6X170lDVueGMs37Dj/6HaR6\n1+o3jHpNOs9CcmcDhx8eo7/7W/96/391TU46VCWWqX3Xm+OcQAXK6G4fx4NUY7IU6s9aq45Z3Lti\nSbB1ItcynH73HM1a5RJ9TyC8XIgngca/k+qCtKFK1cNd5Owa0798EXiWrqdy8DcZ8Ue399dFQw7V\nlQQQwV1JALwhrN+QCw7gXX7APdCFebe6Ndq388AULh5Srzq82PtnOr8pB/Kn5D+A2lr0V0f/dZGs\n/CdH8v9M1kU3xq/XK5Ewu3g69RcWzZClKj4iVwNVwd8Q1ydKjqyzdKeNhqoI1NM4Gw2qMByl/lDL\nvQ3QlKpCBLaI0I9XgOq4LntmQfwNJng2pvGsVyK2pPKiVzX3CMAHEX4Y3SQSV6+6orM/UCIn2n6j\nlrMZXEeLEjYoGVsX9ZCTjZNAslzLcKC91n2lEulmH0dInzTadU/HUqeYZBzpNyEed4Sl18sxVnkM\nN+KUlcgd+qby6uNo2jnnoeGonucoKxGmlD/3CZTfx80wFz2DKg4keNFf8zdAAAMcPQR3lE6QKXgJ\n5b1tzQ7lcaqQI5eKRbHfBFVfjTtZdliEnMS3QRFkvdTPdfxVgf6SXFyLW/EzPnG3o7WFel91gFFN\nhNfRY2QiTY3FXI5pEknv4S/qjncfn17iHE68pCqxDDdD8RvXI9pO0IemRCuPGVtoS42ROkWKhXYJ\nSXH6db9BAyXi2h5rnSK1faPvmWKvV4C5dgnW9qpq8NC659jApFLJzxUQnMSgBnmO15VI5w4i1zLv\nVjd2bG0Gdj5oy1Shx0DLFGXP9jdJs1biXn0mvNlYbdYqF18e0rlvPDJJLXdpjUQuU+YmAVrwCHuS\n1ZSIk2chOzUmcNVDxfYgpwJTcugyJFmpROxci2ltFEkn2wQ2pgbhpJ/PuJaROOnnq12HvZ46K3Ig\nN1XH9fjPAAv+t3Bt/bfkb6tI9nbZT7B1Ehmb+ioVQT+O0MJU9RBfSHUl/IpIqF+8rkKUzGpxG8dg\noQj2x3tjpl2GpV0pqwZv5U51S9a1OcaXesuIyTenGk2WZ29mud6XdOQyk9nE9anrqaqV4c99HN8a\nxbC2ycioRveuKofwfOi3BHKTrTH+zG5xC4Ch74kF+rPWF5jOBsYEpOHoZEww4TzCl4s5Rzic4YXD\n0wfcH/QDd9dtwzmig7Jx0iwErYi+RgW9b8+mPFwsfoHmDzkQ701fp2dcOOhAoZcbDu5FShp5nxoR\nq+/rHMuCTjF0tk1gGL9yNsWd58clfF65F1lZIU1k8YxMukccTbAnGd0kodwOd92No58+EYmGbA09\nQu8Xx+lQE82Nl6ZUJ5WhYauFJpVc7P0zNoXCQrYik2eVLjQ3zaK8TCiXI1Vv0VrjISXVcpJiRaK+\n7Hou8sLLTPGKIPRuLl92Oseeh6K6ubJWgxCucnSrUHwvxn2L1qsEmveRMqpJFCBh1PsxygrnrTH+\nvNf8Np16DWFB0HVezNtKx5mVROJHxCuRN/HnPj7RIp82r0MEb419yendTnxovgszyzKaGmfzUfkl\nwjjP1piWPDopDMJEnLF3LaagUsTsE4pEjH6UxSGe0YyFG0WoxyUoB2tJKmF28aw5Iqjdf+xwHHtX\noRQSRn6jfEZkJfewbV1GeyuRjB+mLWjhU0qMWGiwiR1TwpWL8uUj9qzotpmVu2/Sv49QXCYW5dyW\nqDxITSpxMchjoMtTrvXbyrC3zmJtUEwY59FYdY0Vtt9QXqOJD5HsuneWuKmdqUGDJ3ki9Pqp1iol\nxT4oiL5nipQaHm1VGcWrnVcyckkCcSO+Rf9eHPn6zlw8ZM8UxUYMNctRVNSoeamxeJCCA9qU4UMk\nUkktOfFalFZrcmKHM0mj1rK67Tkq0SIXM2JPGdCtfwIX+2ynZU0q2RbOXEpzYZLNTRKLjfn5vi+J\nxQKVWU+Br1EiFJ6WtlCkNqSzet8NdNqZUBmrUsb/yO/L31aRbHnmT16FNgtSVlOdLqzNo/QnKlf1\nEI+YFUttHeNs7FlBUDdJdw8ba4N5r0pY+7O/ekhktjXFqQoWHBAJ1591AjFb6UanOrbTXfeb0/OA\nNVcIJWV4dz5eJTyKB7Qk6bddnIl1pQYNJTlfc5NMBvzaiZB+oiDxdJQR/TnM092GyCS1rI/w4qpm\nKPddrUhKLiLHWGDvp7kF8bXfGa4QSsuDk+k7qxsvW18lY7d4UdYxG4Au48T9Np0kFrVn2cLKfVR3\n75rOOujEpTF/SHsGyn/DYmgNJlplvEyDCe0/5WKaC/cQwIGIuXtJydUiXa85NZ5mjEkWeQrNZkaC\nyVaniM1SX97qehVPYlh4OZB5T6ZwMc2FeQEipu0hiyOAu4y5NADddiJ5e5qeyFcH0UzjBbqSKjyC\nSjDXLiGu2hGrtd607JDFT0OEwpCmF7PDuicJiVV8eKkrq/3Ewraj02H0RjqhLavChjT6/dyJ6wRz\nyek+a243Z1voEc6tMUaBBIMB1oCCDY/b8mLEt6y6HsROT2+O7Q9lc8djDHd7jLasige05FEzYbF+\ndimQ5B0FzP/uHpscR5CTpcPGCE/aHZlIXkcfPvpRnVonJV50CtQzqKI/hwFIkrVCaqTB59PEfGaf\nyiUnrwbroVW83188J3NvdeNBuAW6lNB5d18+8he0Kz0qrhKQeZViMxkzP45gb/lgHNzF87qycCrT\n9vVk5eAIQuuew5/OdmH1YD/yawRoYmLSWVLi9Rk8NY6L+/ZiTQb52jpcSrDmrWujWDC/O4VlcvJD\nfdiQO5nvI4QH8AhfRrXqRvbSWCWX2w8hx4lz7NkANi7BzyxdwMutRAMvgCjN3uxe5oL7npnYOBkp\nF/XjW39AtyqPhmjFacujUEiFaT1/0yMe4ctI9yiK62DuvTnOwYRmzL8t4PaOJDLw05f0HZBF5+Pj\nOZ7oSXmaFJPpztzPtiHAIpURDoKm58TPh+hhfJdFq+4g9xXXYGBaxaQlTzjMQH4caknZzTyCCec/\nIv94JP835fHqoRzqtpdnC5OQWQtX2ImXNG/gpu9Z54HtDn/cEEVJcio4UNodvXsveXRbhLq2fuBC\nfJEJgznAeysfYa1TxP0rljS9VEbUZFFPcOeVPVU/CNTJb7+6cCbFHVAR3L3l+BwZ1bREWKWP86x4\nJPHj8lHRw2Hz9/exJwWfMQXUoEEGNgRVhdPL8RouB2RcGP4LOnpVVC9pSSuLNG6s3YGxvIw07Gh2\noxUP8Se831YAoqdtpPWjBMaxnWHthcWbjwmj+YWXRSZYSrPJ++4lsQgW3bvOHchZ84K8Ch3kRgZI\nlogXy9NRWPG9tw9nQ3YwyLRwLM3DJzeGHZ0OYekg6lumbIzm3hlTjvwSyIADUjxtyjnQdR+7t+zm\nQ3bQi994muzATdqTWmLI3g1NlPO/48oiknBg9W+3sDXPx+hUZw7+eo7MOU/Y+NYp4k7EMqHlA873\n3sGaxE8o/NIZgGDEfU2uPkzR7mSmSjaRji2PacEHPjeorpEysUsS968kK63fosOq0KXGT0swMqtg\nbvIVqqpSmHilL0deuDFVsok5n6hCl/vivTEmn9XTW2F1L7JuLo05ePUg92ND+ezdxnkrM+sySoo0\nlTDnaj85tQXVfPitOO4jfKlBRsxDY7SaG9DB5iWr2lxAJ9iUUvRIwJXPHnQg1DaBCx7dOaOzklnz\nbvHtCmGE/OK8HYBNHU5QadMXk8ISSprqYs4rsru0JqXEiCMnm2Alf8WdYUJ5ZSbr0nnoMEzIQ1e/\nmtGrkinI0cJAR4HFhU7cu2xJWY0mIW6qkFDKXOEZlZdqgHswk8P7sPO5egO4hzl1IbrMGCbUFe3u\nrIPMS6UKjjVgak6aENWI9Xjj4hZU1mowukkkq6f4IAvupnaOE/RhTl3NjgGF6FLKwU9c+HacMU76\n+dxZsY2a8gryvntJC9MsTLXK2JMs8lG/jKskrVyLlQvaYGBcxWD2k20+jHs9BtOPo7xAvKPdf9Hk\nH/nX8rdPtv8SsIUxd9/5FyOEtAjMVoP2/qvEZ70Eds3g1jkVvNOxSRFJzxvUUNi1gNSoN4yE1wsT\n62knBnAIHfcmdG8tZ81ZIyJzVMdv3yOdG6fVX0rr733ImPoIU61Scit0WR90kpyJ5nz6dhv+SPS6\nW1By5lWj71e0vsDHEWFYLG+KdOVdMsvUKeEnLn7C5uXef3hsW+diZT8UW1JJQ73o7vyB/fRZO5my\n67lvGo7URJPavKo3bgOQ6MpQlDZuVKYhqaFX+3iOXW/yhlEqmX1dk2+CXju+ZRMlWyzA254P2BbT\nmOX5dfEPecWDcIt/uV9DMSGXPFTUKGZapUp4rqtXAfFPjTBf4kH2sljMP/Uk+9MYtfH2veSknKxk\n7IfP2PGl8Fotv/Aia57Ii4yYFavWEK3hNTYEPUxqdo+fot/cLVBbr5ryEg22hR7h7bqWwQC2v/iT\nNuZ32vQ1ENudLUkb/S/JZQEwmuBIwdakf7nf0OnP2fed+G3rWwDr9bCk5LQwEk3nulH79V1lq4N6\neXtBNNsawIRBdPTMZuO/n2xf9ldH/3WRLPkn2f5fF00XXQItk4US0RGFZxuDf1MmCBuKoaaI29cr\nEaewII732M3DsgaLtaaE5QEX0bYRPqWFdomy2U/sVUOu9N2GUR0WPjVXtThM5Cd6V68DRHJWJSoF\nL+gaxOd6LqMYk2BKUjPR2VkIORloUok+Iqxx47QNO8NVNPf6FJExVSSGy93NMRhgzYyHDWg56qWp\nen3E+18/pE32XfQMxWLqqJ/PmvMiKf9xhPA49LqYc6jbXnQ1KmkblE6rtiImPyg5EluXYj7+KQJP\nvzzcvAswIRf9utbDHWxeYlVchBHCyrXQLOTutM3Y7VNZ8V3GTaZvYTgj2YV+H3V016yDiUiKKkBT\nm0t9thOiFcEq4y9pjkoh62mW8dbYlxA0Udm+10qnGIkm6LZSsN5UvN2/Rp5RK6R7MGgTbbjNxkna\nmFqV42UiFGmnQl98sg4o97vWbyvmNnVtfU3EfRlQSOn7KxtN7fMo8YxZ2peqfd/N/gXuhjlYrvHG\nwyibde1PETVEtN4tlxmgr1mBoYcm7a2SyKnQJdBSJM2P+uxHoiujdOVjzIP0aDGoce+bpQZrAZRK\npDunMVxxTbk9fLOYUyO5eL5rwtOw1xPFpB/XXqC/czROnoUceOGFZx18WW6pwSL/q3heFYrFw00k\n7r94qE5/f+zw1Lq/GhuqJpYqpFjv0ZMbbX9djEwrkBmY4rPrqNr3FrZl7I06rQQrePIMJDIuHxUG\nSVDPdAKaCE+z5HQWWpTjZphLaNRl8jEhb+RS7F1VwJKLG2zY2fkQAD93OsyF3j+j5/If8kj+CW39\n3xQNe22qCotp+a4Pdt3FQvnhtY5YOZRiTzLOiLhyl2bJFFZpE9o/Rcl5ZRGzhRXVnSmuMEeTShz0\nCnCres53d5shySrD0z+P/W03saPOjTdvWsnwKacot7fgLcdYanJUVu5mJnEj05du/RM5EuNEX6dn\nyD30CO2fqqxD2ffUGZDg5ClechevAqrz8ohybc3sy2vYHnqUKuQsaH0HPd0KLMlk9KBZaLrootfT\nkqCQbHo4PMeadPTlxuy0/hZKcrB2LCWkazJNiWbBd/fg2XnkVIC2AT6a0ayZ68e9R1ZICsvRN6ok\nqdiYZb3U4aR2C3bx7TU3SqvlSDItqJWLR2rQ9n5Y2ZfhUZ2Nc2YGxvFpoKVDcZUWfvJoPlx2nxod\nKTXIcCaBgB6VjN4YROFQFdJMR5LJFWNf9jOEDqnXkejKaNsyn+72cawb5ISrxkts7HKYfrYdURXu\nBPuBu7MGw72jcDXMpaPRSwp2JON7NpGbtMewjyUl3d2RmHvw4rwG0waLRe7Xfo5EpQnPSO6pj/+1\ntej2t+PI9FPYukmJyRd04l3uXCLXTdy/vWsxwSff4cvLQvFJ80rRklUjowaLp9/gbyYACtothQIx\nqSqjq/0LslJ0lfcXZhdPZYAWcYVmaHx8k4xSfS6lObMuvQ1m1mVY1qRSrOvMUOktOrmKkGJloTAW\n2qTMw6E0Hh2NauwKn/OiRQP6Hbkefbxi2VY0AGN5GWbWZcSPWEe+ZXPiCk3p7xxNoMNjMoytQCan\noFIbc5syejRJJ1uhiyEFyIoEYisjUY9eXuFICl5hbKhF1NwNbHzQgtoOe9B01eXRIwswsCS22AwH\nf10lXfyK+/VoSAkuzQrQ72dNU3sFof1TcDNJI7RfKk4ehfzIu8i9DJBKFfR3jka/t1BuXpJoLMlE\nQ7MWs6oSNGV5GLQwRIYKWWZXkU9UXFt0zI3pZh9HOjbILAVFTEjXJBKv6nE3VnjqcirwtczmRaEp\nh86KAt27T8HKUSj2VW3PkaJryZpqkZdafKklH55vg4nd73u8/4hK/vahra2hR5jQwCXX1q0Wcd/f\nE6kG7bomM2hyPB8MVFlhNvql9JmbwI9L3xzOOd97Bz9Ft1TrjGdpV8rBVr8ScuzNNAzWOkVklBkw\nudldfogOQJ8iNt6+xdi2XZX7dC1uzjl9dRoLmYWcmlciaW2iVUZehTrEFsDbJIsha14qQ1sbnkfy\ndJ+Uwz+6kp6oDnkM6JTJ3UtW7B11EDujIjqdmcayJWdZOC4Yl0ehJPhcBiDU9SW3s+zUuI/qxc0w\nF5mkFp3mCiKvi/CJnU4G2OiTGq+PkbycgkptZq6O5Nv5Ig7u75XEg6cCVRT8VhrXfrPFxqmE9EQ9\njMwqKMhRr2ZuYZqpBpYwMKykqFC9lmRG89tsehqAoUUlOZmN56VehkyL48D3bsrWqxZ2pbxK1cVO\nr5DUEhVNiJV9KZ8eTGTtkU7Efp7xe4dDaqpJbe6fW5S0dKrZOegIQ3YOxjfolXK+GopDkyKS68Kj\n3q1zqIqF2AIzPIyy8R+Tx+FLLWlaEMejFCukRhrUFlSjG2qm7PjY5ZwT5+e3hvvCw3L1KiD9qZxq\nuVyNHcGteQHjRj9lyQKBVBP911Xb60NHvmYZauHVPxIb3SLSS/9n9OzuLfKJi1Jx4J3utZOkYiNm\nuP9GxVbRqro+HGexvCmvFgs2iOihG2h2cQ3BlzUIu/ALN3ZbcueBDQWV2mxrt4e3H70HJTmNzmez\nxY/0dx7y894zjBt2698Pbf2JsqX/tEjm/xPa+q9Ll6uW7J10iAW9FnG8x24cPYpoNsIHl2aFLG55\nBbs+IdiRgrNBHgv9wpWVuNRWc/OMDQt+XMvxHrux/lEsekFNEvlxqTcb9lxWnsOxDq8+1SsCw51a\nlFRpoquvWkz6GDwjvUyftz0fIJUqGOchejt8czwcWZuhGMgrcTjWhv3RLjQhFjujCt4ODKPLkGTc\nec6X6xKIOSsWU+e9Kt6vGp0WSA006HNcToB5GkOmCbDAdO87HO+xm1kzwnHLu0lpnBQzqzJGvR+D\n/J0kivI0eXtBNGbz3DkzdhdDw614NPh73LyFJ9RBmsDwnhs51GQzX44TseQpGUfZdvMBm348z+c+\n52nukcPKsCg6c4HP2whOKg+tJPrsKmGk9hE0Yqpw0Cvmx/VnOZFzidR44Ql4tRbhl6Qv68IebkGk\nz+hNWMcYenOc2IfG7B15guHza7DQLhFKRFOHdt3TlXxKP/iJOpIhviIH8FaSE3O+FnM6wDkaGdXY\n6RUxVLGXQK1kmkif03NUIhIUjBxxn2M9dtNzVCJfH72O5HQFoyts6fVxHlrSanrrx7D+xBUs37Vj\nMPvZOe84tyr2k1npy9S2zag5/oz1e1W/fWC3DFp3zgSXtphaldNRO5bmxz3B1IlFm+4q6U8ADo7c\nT3srQcPz69TD2Nvms7XNOJoY5mD8OI87P+4l+LhAonn45hE2wQ4t7RreW/mIfRMOYlZQzLwTItm/\nvdNR2nXPwNq9BQu2P8CEXBa5XWDwPgOGtxdeTXurJM7P8ebqd6InSsuOWRTmyQm0zcDQpJJOy3WZ\nc0WD4TNj+dj8EtkpNSz7+Ta75h5DX7OS4F5pBPYUIa2P65BprY43Zf6Ek8i1avBD5EaMxtrz9eFr\ngqUZ6PGBIaBg/t6HrDmqCrGt8tgNrYbSjKcMkR7GHxHiHTDxBcd77Gbc8WL8ZWnK8KPJdGcGnBzI\n6qvNaBW8h9FzY1iyOYJ51Zcxsy6je95RWv7iytgPnnE53Rmy4wm6soekDEMeZ1oy3fsOIdaJvKiw\nJdhAFU7+NED0jLEmHedFAt311Tdvzg39I+ryt/VINl8NYX4Hn0bV6gH2adxNUa+s1myiR9VzgSfX\nllUJLL1pBqklhtjrF6pZYn5m6RgG1XL1mHriuNE1UIvMUY/qJLEIakmrMdUuo0fpfrah7qHUW8GW\n9qVqoRENB22qk8XCW+9JtTJP415RE6hQx79bk462gTblReVq6BhlH4c6sSKDTKyV92lJJuUmJhTm\nyTElh1xEmKeNZQp3suy5138ji+905mRaU1w1U0ipsqDyNa58ORX4W76iqErO0zxL5N4G7Fm1iU9G\nd+Zxgepa9nX+lSkXuyrPAah5Hg5aqfg4KPgt7vVeqdCUaK6MPaHGIJv2MED1JwAAIABJREFUyVps\nl85R289Br4DkEiNsdYugtLAuwa9gYtMHbK7rHePdJpe8xxo8XvgjzX6chplVOTmZWjhV5GFe+pIH\nxa6ko3pGmrbM49l9E/zN08mr0OZl0Zt7fdfPtVy7hs9XX2PurI5qc9nwtzI00iS2QDybehqVlFTL\nsSSTLKxEyNPHluxHVXXJYJXH4mWSRVkTAxLu6NDLMZaTSR44ehShKa/hxWNjJZO1lk41DpoFxBWa\n4WaYi9RZSm6snOJKORW1Gnx9+BpzB9QVvroUk5agDqZoaZ5Gup6R0nttZZ7GvWxbtTkG+N5iOVNf\nLX7jfPxPxEGSQrLCnpHsYq/l29RkicLKn7ufpt8ZVcW9qp+Puhw/fZT3hwbzvFC966GWtwEVT4oa\n7R/edytDj/XAyriWh/lb/n2P5Ou/Ovqvi2TuPx7Jf10WRcwgB3OMOo1SWofm2iXEZpqyNOASBnVJ\nYV39KqqelyirYctrNGlhmkl0qTMVFTVImomH1kqnmNFzY7B/0IbKMhlJS9coz9XU+BUTSsxBz5xj\nw0QoQYEUO+1MXIinuVMSFbUapJcaKJXI8BpHpix9DCiUoZRx4+4DCmVlspksj4HFToQNSqadcTLP\nhm1A0kKGhqWIU1s102XrMdGDI1dqwUTna/gPEfelLavi0213sLUvY4L3Jdx+8UZmrYWPfQlNfPKx\nqEmnh/VT5FRSmFdHPtjvCBuCTmJsXkFLE5G8nlszliX9ztLV/gVl6FGJFgEWqWj5GrKlo0iOWpGJ\n7nxXCvIqhbWXksD6PrY4GYi+FXsensHDN5+hF4cz4CNVQShAh8AUtHSqaW6SxZWBBwjoX4Z/yCu6\n26v6RAR2zcB/mIT952Dy2EhahWbhqJ/PqEdDcPIo5OvD1wjsmkGYXTzaDp4oJi+l3TRN0trMw5g8\n2nXNUCoRE3J5aehBR5tEjJNL6NguDtv0PLS0a2l6wo84WVO0qKCN0QsOdd2Db9Nk9Ayr+ND3Omkl\nBnzifYropZuU1dGu3gXo20kZ0yQSuUzBgqUR7Ag6zNxZHVn8UwQ+phk8ybXEtC4BvbzzDiw6WxNb\nYE5byxQ8/fN4/1oqWLjhZFHN8Z2HMTMuJvtRFSZaZQztmURnz5d4jWtNj5+MyM+rwjg+n4/OxJLe\n3AqnlmVo61Yz1/g6Xe1fsLb9aSx1itGoqoV5IsxaVFhFrokDduXPQQv8/j/2zjs8iqp9/5+tyab3\n3gkEQi+hQ+i9NxFEUVGwF+xdRLGggtiFVyygFGkCgnTpvXcCAVJI732z+/vj7M7sZDcJvq++v/cr\n3NfFRXbmzOzOmZnznPM893M/TQuZPrIru3//iSin67zgtpo9vT+k9HVRHjjctYAvVm3H46osZurj\nXMbM8UcZEnuBEpMwOlHuefRoJ4gtAGENiukXdonej1Sy7rdvpWMne4jnpG9YErGqJBp5ZhPjIuKR\nXgbRL+laYaSu9OpFQstrjOIX7ngyieEb78Q/pJTve4q8nMoKDU813EzLLlnENs+X3s2XZ3ShoMoJ\nQydh5N11FcwduIFWWWfBS0z6gvobcG7vhYFS7ljTnxA/qIyVJ263UTtu2RXJvC4JPLZ7EC19bnA8\nV15RxHlmMznuGC8eEAwmF20lpUY9UdF5JF+RZ5phrgWkWGZdAJogJ6pvVOAdUM6wycl8935jaV+P\nESlsXxXGA5NPMD46ld6vD1T8nv7jr7Hx5xoaVRqIMORzrVj2C2vDDRivl/Hr0o0MHdefqU0O8f2A\nHyj7eK7UZv3ARQz6bSKuHlW0753BxcmjSBl+AIBYjxwuWWZkY1lKqxedeXnWMGqDVd8JoHGTXJx9\nqjm22x8fpzJybeIu8Qm5igp+QaSThze0CKDiRCFOLTyoOFFIKCl4eeulTGjrTBtEMtmMHkeYvH0k\ntugbmoRH6lGMI1qxelUsA8IvsuG6Y9ru2x0+5eX9j/LrgMV8d6EVyy/L2lztOMghEpjywEke/uw0\nr9zXkRcKt7G4ohNfbmysOM+2oQvp+etk9pYvZ8b9CVK1vfANHbk+YJ/UzrYGzPCoc6xObswdsRvZ\nmN+D/Gx5VWatm2KtOROyqA1pE48QTBpOjd1IPifHXIZHnWNzSgz3vXWOeS+24P0Om3huf19Ge63l\nl3xZWdgRPuu0mkf2DieUFFIJI6SHM2nby/Gf1YSsF2UZlsZeWZzL98evRXuyTxyQtrf2vMqNKh8K\nuzfAc8NRBR37YM7P7H7Ah6iSHF450ZFZLfcydMMExfe/0Gonc052pLy6dqbTjmHfsr40jgGGC/T8\ndTIAox5MYsXXFm07i97X+oE/Mui3u+q8Xiut2XVQAPEHj0rqA97+5eRlOfNa2+18nZXAjWs3J3MS\n8EE8mc8Kt+inXdfx6C6rvtpfoLX1D1+R3LKG5Nm5Q/ngiTa8tjuJGV0a2LUxuFVJQeOm3pm0KNrB\nT8axkmGxwrmDF+X78+2OD+M6Kcjy7YbO3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OgbuhKcnoo5WENlhVqia+rVRpw8TBTl65k1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rtQ0FJjQRi3ER7sxuvZ9YTjAyXCyoWmoLHgNHac9caZ5qq4ZqWh2+jAENd/7ah+dZIH/3U2IM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9d+dBv7VWHdLv0efnT4hx79NQ3lGL43Lvd7C6Dafs92Va3WFnMxxDYf35OadeHz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kx0sCBh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\nFiQMwzBMVLAgYRiGYaKCBQnDMAwTFf8P+kJgC6CNyrwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11e9cdf10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print 'Average rating for movie 1 (Toy Story): %0.2f' % \\\n",
    "    np.mean([ Y[0][x] for x in xrange(Y.shape[1]) if R[0][x] ])\n",
    "\n",
    "# \"Visualize the ratings matrix\"\n",
    "fig = plt.figure(figsize=(6,6*(1682./943.)))\n",
    "dummy = plt.imshow(Y)\n",
    "dummy = plt.colorbar()\n",
    "dummy = plt.ylabel('Movies (%d)'%nm,fontsize=20)\n",
    "dummy = plt.xlabel('Users (%d)'%nu,fontsize=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Throughout this part of the exercise, you will also be \n",
    "# working with the matrices, X and Theta\n",
    "# The i-th row of X corresponds to the feature vector x(i) for the i-th movie, \n",
    "# and the j-th row of Theta corresponds to one parameter vector θ(j), for the j-th user. \n",
    "# Both x(i) and θ(j) are n-dimensional vectors. For the purposes of this exercise, \n",
    "# you will use n = 100, and therefore, x(i) ∈ R100 and θ(j) ∈ R100. Correspondingly, \n",
    "# X is a nm × 100 matrix and Theta is a nu × 100 matrix."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2 Collaborative filtering learning algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Read in the movie params matrices\n",
    "datafile = 'data/ex8_movieParams.mat'\n",
    "mat = scipy.io.loadmat( datafile )\n",
    "X = mat['X']\n",
    "Theta = mat['Theta']\n",
    "nu = int(mat['num_users'])\n",
    "nm = int(mat['num_movies'])\n",
    "nf = int(mat['num_features'])\n",
    "\n",
    "# For now, reduce the data set size so that this runs faster\n",
    "nu = 4; nm = 5; nf = 3\n",
    "X = X[:nm,:nf]\n",
    "Theta = Theta[:nu,:nf]\n",
    "Y = Y[:nm,:nu]\n",
    "R = R[:nm,:nu]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# The \"parameters\" we are minimizing are both the elements of the\n",
    "# X matrix (nm*nf) and of the Theta matrix (nu*nf)\n",
    "# To use off-the-shelf minimizers we need to flatten these matrices\n",
    "# into one long array\n",
    "def flattenParams(myX, myTheta):\n",
    "    \"\"\"\n",
    "    Hand this function an X matrix and a Theta matrix and it will flatten\n",
    "    it into into one long (nm*nf + nu*nf,1) shaped numpy array\n",
    "    \"\"\"\n",
    "    return np.concatenate((myX.flatten(),myTheta.flatten()))\n",
    "\n",
    "# A utility function to re-shape the X and Theta will probably come in handy\n",
    "def reshapeParams(flattened_XandTheta, mynm, mynu, mynf):\n",
    "    assert flattened_XandTheta.shape[0] == int(nm*nf+nu*nf)\n",
    "    \n",
    "    reX = flattened_XandTheta[:int(mynm*mynf)].reshape((mynm,mynf))\n",
    "    reTheta = flattened_XandTheta[int(mynm*mynf):].reshape((mynu,mynf))\n",
    "    \n",
    "    return reX, reTheta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 2.2.1 Collaborative filtering cost function and 2.2.3 Regularized cost function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def cofiCostFunc(myparams, myY, myR, mynu, mynm, mynf, mylambda = 0.):\n",
    "    \n",
    "    # Unfold the X and Theta matrices from the flattened params\n",
    "    myX, myTheta = reshapeParams(myparams, mynm, mynu, mynf)\n",
    "  \n",
    "    # Note: \n",
    "    # X Shape is (nm x nf), Theta shape is (nu x nf), Y and R shape is (nm x nu)\n",
    "    # Behold! Complete vectorization\n",
    "    \n",
    "    # First dot theta and X together such that you get a matrix the same shape as Y\n",
    "    term1 = myX.dot(myTheta.T)\n",
    "    \n",
    "    # Then element-wise multiply that matrix by the R matrix\n",
    "    # so only terms from movies which that user rated are counted in the cost\n",
    "    term1 = np.multiply(term1,myR)\n",
    "    \n",
    "    # Then subtract the Y- matrix (which has 0 entries for non-rated\n",
    "    # movies by each user, so no need to multiply that by myR... though, if\n",
    "    # a user could rate a movie \"0 stars\" then myY would have to be element-\n",
    "    # wise multiplied by myR as well) \n",
    "    # also square that whole term, sum all elements in the resulting matrix,\n",
    "    # and multiply by 0.5 to get the cost\n",
    "    cost = 0.5 * np.sum( np.square(term1-myY) )\n",
    "    \n",
    "    # Regularization stuff\n",
    "    cost += (mylambda/2.) * np.sum(np.square(myTheta))\n",
    "    cost += (mylambda/2.) * np.sum(np.square(myX))\n",
    "    \n",
    "    return cost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost with nu = 4, nm = 5, nf = 3 is 22.22.\n",
      "Cost with nu = 4, nm = 5, nf = 3 (and lambda = 1.5) is 31.34.\n"
     ]
    }
   ],
   "source": [
    "# \"...run your cost function. You should expect to see an output of 22.22.\"\n",
    "print 'Cost with nu = 4, nm = 5, nf = 3 is %0.2f.' % \\\n",
    "    cofiCostFunc(flattenParams(X,Theta),Y,R,nu,nm,nf)\n",
    "    \n",
    "# \"...with lambda = 1.5 you should expect to see an output of 31.34.\"\n",
    "print 'Cost with nu = 4, nm = 5, nf = 3 (and lambda = 1.5) is %0.2f.' % \\\n",
    "    cofiCostFunc(flattenParams(X,Theta),Y,R,nu,nm,nf,mylambda=1.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 2.2.2 Collaborative filtering gradient and 2.2.4 Regularized gradient"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Remember: use the exact same input arguments for gradient function\n",
    "# as for the cost function (the off-the-shelf minimizer requires this)\n",
    "def cofiGrad(myparams, myY, myR, mynu, mynm, mynf, mylambda = 0.):\n",
    "    \n",
    "    # Unfold the X and Theta matrices from the flattened params\n",
    "    myX, myTheta = reshapeParams(myparams, mynm, mynu, mynf)\n",
    "\n",
    "    # First the X gradient term \n",
    "    # First dot theta and X together such that you get a matrix the same shape as Y\n",
    "    term1 = myX.dot(myTheta.T)\n",
    "    # Then multiply this term by myR to remove any components from movies that\n",
    "    # weren't rated by that user\n",
    "    term1 = np.multiply(term1,myR)\n",
    "    # Now subtract the y matrix (which already has 0 for nonrated movies)\n",
    "    term1 -= myY\n",
    "    # Lastly dot this with Theta such that the resulting matrix has the\n",
    "    # same shape as the X matrix\n",
    "    Xgrad = term1.dot(myTheta)\n",
    "    \n",
    "    # Now the Theta gradient term (reusing the \"term1\" variable)\n",
    "    Thetagrad = term1.T.dot(myX)\n",
    "\n",
    "    # Regularization stuff\n",
    "    Xgrad += mylambda * myX\n",
    "    Thetagrad += mylambda * myTheta\n",
    "    \n",
    "    return flattenParams(Xgrad, Thetagrad)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Let's check my gradient computation real quick:\n",
    "def checkGradient(myparams, myY, myR, mynu, mynm, mynf, mylambda = 0.):\n",
    "    \n",
    "    print 'Numerical Gradient \\t cofiGrad \\t\\t Difference'\n",
    "    \n",
    "    # Compute a numerical gradient with an epsilon perturbation vector\n",
    "    myeps = 0.0001\n",
    "    nparams = len(myparams)\n",
    "    epsvec = np.zeros(nparams)\n",
    "    # These are my implemented gradient solutions\n",
    "    mygrads = cofiGrad(myparams,myY,myR,mynu,mynm,mynf,mylambda)\n",
    "\n",
    "    # Choose 10 random elements of my combined (X, Theta) param vector\n",
    "    # and compute the numerical gradient for each... print to screen\n",
    "    # the numerical gradient next to the my cofiGradient to inspect\n",
    "    \n",
    "    for i in xrange(10):\n",
    "        idx = np.random.randint(0,nparams)\n",
    "        epsvec[idx] = myeps\n",
    "        loss1 = cofiCostFunc(myparams-epsvec,myY,myR,mynu,mynm,mynf,mylambda)\n",
    "        loss2 = cofiCostFunc(myparams+epsvec,myY,myR,mynu,mynm,mynf,mylambda)\n",
    "        mygrad = (loss2 - loss1) / (2*myeps)\n",
    "        epsvec[idx] = 0\n",
    "        print '%0.15f \\t %0.15f \\t %0.15f' % \\\n",
    "        (mygrad, mygrads[idx],mygrad - mygrads[idx])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checking gradient with lambda = 0...\n",
      "Numerical Gradient \t cofiGrad \t\t Difference\n",
      "-0.766778776704058 \t -0.766778776703673 \t -0.000000000000385\n",
      "-0.523398454959079 \t -0.523398454966595 \t 0.000000000007516\n",
      "-0.803780061460202 \t -0.803780061452057 \t -0.000000000008145\n",
      "4.742718424690651 \t 4.742718424695921 \t -0.000000000005270\n",
      "-0.832407133088964 \t -0.832407133096985 \t 0.000000000008021\n",
      "-0.568195965513496 \t -0.568195965515757 \t 0.000000000002261\n",
      "-0.803780061460202 \t -0.803780061452057 \t -0.000000000008145\n",
      "-0.766778776704058 \t -0.766778776703673 \t -0.000000000000385\n",
      "2.263336983912012 \t 2.263336983921972 \t -0.000000000009960\n",
      "-3.050990064075165 \t -3.050990064071511 \t -0.000000000003654\n",
      "\n",
      "Checking gradient with lambda = 1.5...\n",
      "Numerical Gradient \t cofiGrad \t\t Difference\n",
      "-0.197479281052182 \t -0.197479281036198 \t -0.000000000015984\n",
      "-0.647874841526175 \t -0.647874841514519 \t -0.000000000011656\n",
      "1.092897577699148 \t 1.092897577688307 \t 0.000000000010841\n",
      "2.101362561361952 \t 2.101362561388682 \t -0.000000000026729\n",
      "-0.197479281052182 \t -0.197479281036198 \t -0.000000000015984\n",
      "-0.955963393440840 \t -0.955963393432562 \t -0.000000000008278\n",
      "1.092897577699148 \t 1.092897577688307 \t 0.000000000010841\n",
      "-0.197479281052182 \t -0.197479281036198 \t -0.000000000015984\n",
      "1.092897577699148 \t 1.092897577688307 \t 0.000000000010841\n",
      "-0.108611088780464 \t -0.108611088785302 \t 0.000000000004838\n"
     ]
    }
   ],
   "source": [
    "print \"Checking gradient with lambda = 0...\"\n",
    "checkGradient(flattenParams(X,Theta),Y,R,nu,nm,nf)\n",
    "print \"\\nChecking gradient with lambda = 1.5...\"\n",
    "checkGradient(flattenParams(X,Theta),Y,R,nu,nm,nf,mylambda = 1.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.3 Learning movie recommendations\n",
    "##### 2.3.1 Recommendations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# So, this file has the list of movies and their respective index in the Y vector\n",
    "# Let's make a list of strings to reference later\n",
    "movies = []\n",
    "with open('data/movie_ids.txt') as f:\n",
    "    for line in f:\n",
    "        movies.append(' '.join(line.strip('\\n').split(' ')[1:]))\n",
    "\n",
    "# Rather than rate some movies myself, I'll use what was built-in to the homework\n",
    "# (just so I can check my solutions)\n",
    "my_ratings = np.zeros((1682,1))\n",
    "my_ratings[0]   = 4\n",
    "my_ratings[97]  = 2\n",
    "my_ratings[6]   = 3\n",
    "my_ratings[11]  = 5\n",
    "my_ratings[53]  = 4\n",
    "my_ratings[63]  = 5\n",
    "my_ratings[65]  = 3\n",
    "my_ratings[68]  = 5\n",
    "my_ratings[182] = 4\n",
    "my_ratings[225] = 5\n",
    "my_ratings[354] = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# I'll re-read in the data because I shortened them earlier (to debug)\n",
    "datafile = 'data/ex8_movies.mat'\n",
    "mat = scipy.io.loadmat( datafile )\n",
    "Y = mat['Y']\n",
    "R = mat['R']\n",
    "# We'll use 10 features\n",
    "nf = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Add my ratings to the Y matrix, and the relevant row to the R matrix\n",
    "myR_row = my_ratings > 0\n",
    "Y = np.hstack((Y,my_ratings))\n",
    "R = np.hstack((R,myR_row))\n",
    "nm, nu = Y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def normalizeRatings(myY, myR):\n",
    "    \"\"\"\n",
    "    Preprocess data by subtracting mean rating for every movie (every row)\n",
    "    This is important because without this, a user who hasn't rated any movies\n",
    "    will have a predicted score of 0 for every movie, when in reality\n",
    "    they should have a predicted score of [average score of that movie].\n",
    "    \"\"\"\n",
    "\n",
    "    # The mean is only counting movies that were rated\n",
    "    Ymean = np.sum(myY,axis=1)/np.sum(myR,axis=1)\n",
    "    Ymean = Ymean.reshape((Ymean.shape[0],1))\n",
    "    \n",
    "    return myY-Ymean, Ymean    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Ynorm, Ymean = normalizeRatings(Y,R)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warning: Maximum number of iterations has been exceeded.\n",
      "         Current function value: 72872.076677\n",
      "         Iterations: 50\n",
      "         Function evaluations: 80\n",
      "         Gradient evaluations: 80\n"
     ]
    }
   ],
   "source": [
    "# Generate random initial parameters, Theta and X\n",
    "X = np.random.rand(nm,nf)\n",
    "Theta = np.random.rand(nu,nf)\n",
    "myflat = flattenParams(X, Theta)\n",
    "\n",
    "# Regularization parameter of 10 is used (as used in the homework assignment)\n",
    "mylambda = 10.\n",
    "\n",
    "# Training the actual model with fmin_cg\n",
    "result = scipy.optimize.fmin_cg(cofiCostFunc, x0=myflat, fprime=cofiGrad, \\\n",
    "                               args=(Y,R,nu,nm,nf,mylambda), \\\n",
    "                                maxiter=50,disp=True,full_output=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Reshape the trained output into sensible \"X\" and \"Theta\" matrices\n",
    "resX, resTheta = reshapeParams(result[0], nm, nu, nf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# After training the model, now make recommendations by computing\n",
    "# the predictions matrix\n",
    "prediction_matrix = resX.dot(resTheta.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Grab the last user's predictions (since I put my predictions at the\n",
    "# end of the Y matrix, not the front)\n",
    "# Add back in the mean movie ratings\n",
    "my_predictions = prediction_matrix[:,-1] + Ymean.flatten()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top recommendations for you:\n",
      "Predicting rating 8.3 for movie Titanic (1997).\n",
      "Predicting rating 8.3 for movie Shawshank Redemption, The (1994).\n",
      "Predicting rating 8.3 for movie Schindler's List (1993).\n",
      "Predicting rating 8.3 for movie Star Wars (1977).\n",
      "Predicting rating 8.2 for movie Raiders of the Lost Ark (1981).\n",
      "Predicting rating 8.2 for movie Good Will Hunting (1997).\n",
      "Predicting rating 8.1 for movie Usual Suspects, The (1995).\n",
      "Predicting rating 8.0 for movie Wrong Trousers, The (1993).\n",
      "Predicting rating 8.0 for movie Braveheart (1995).\n",
      "Predicting rating 8.0 for movie Casablanca (1942).\n",
      "\n",
      "Original ratings provided:\n",
      "Rated 4 for movie Toy Story (1995).\n",
      "Rated 3 for movie Twelve Monkeys (1995).\n",
      "Rated 5 for movie Usual Suspects, The (1995).\n",
      "Rated 4 for movie Outbreak (1995).\n",
      "Rated 5 for movie Shawshank Redemption, The (1994).\n",
      "Rated 3 for movie While You Were Sleeping (1995).\n",
      "Rated 5 for movie Forrest Gump (1994).\n",
      "Rated 2 for movie Silence of the Lambs, The (1991).\n",
      "Rated 4 for movie Alien (1979).\n",
      "Rated 5 for movie Die Hard 2 (1990).\n",
      "Rated 5 for movie Sphere (1998).\n"
     ]
    }
   ],
   "source": [
    "# Sort my predictions from highest to lowest\n",
    "pred_idxs_sorted = np.argsort(my_predictions)\n",
    "pred_idxs_sorted[:] = pred_idxs_sorted[::-1]\n",
    "\n",
    "print \"Top recommendations for you:\"\n",
    "for i in xrange(10):\n",
    "    print 'Predicting rating %0.1f for movie %s.' % \\\n",
    "    (my_predictions[pred_idxs_sorted[i]],movies[pred_idxs_sorted[i]])\n",
    "    \n",
    "print \"\\nOriginal ratings provided:\"\n",
    "for i in xrange(len(my_ratings)):\n",
    "    if my_ratings[i] > 0:\n",
    "        print 'Rated %d for movie %s.' % (my_ratings[i],movies[i])"
   ]
  }
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